"adopt"<-
structure(.Data = list(country = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 
	8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
	25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39), 
	.Label = c("Africa", "Belize", "Bolivia", "Brazil", "Cambodia", 
	"Canada", "Chile", "China", "Colombia", "Costa Rica", 
	"Dominican Republic", "Ecuador", "El Salvador", "Greece", 
	"Guatamala", "Haiti", "Honduras", "Hong Kong", "Hungary", "India", 
	"Jamaica", "Japan", "Lebanon", "Mexico", "Nicaragua", "Oceania", 
	"Pakistan", "Panama", "Paraguay", "Peru", "Phillipines", "Poland", 
	"Portugal", "Romania", "South Korea", "Taiwan", "Thailand", 
	"Turkey", "Vietnam"), class = "factor"), visa88 = c(28, 6, 21, 164,
	0, 12, 252, 52, 699, 73, 54, 41, 88, 10, 209, 41, 161, 49, 6, 698, 
	30, 69, 23, 123, 5, 15, 10, 23, 300, 142, 476, 51, 17, 0, 4942, 56,
	75, 11, 1), visa91 = c(41, 4, 51, 178, 59, 12, 263, 62, 527, 55, 
	50, 11, 122, 5, 324, 52, 244, 40, 25, 448, 39, 83, 17, 106, 11, 16,
	9, 10, 177, 722, 417, 95, 10, 2552, 1817, 55, 127, 6, 17), visa92
	 = structure(.Data = c(28, 33, 32, 5, 8, 27, 9, 11, 23, 29, 24, 22,
	3, 35, 25, 26, 15, 16, 13, 19, 17, 31, 8, 1, 33, 4, 7, 7, 14, 18, 
	21, 2, 35, 6, 10, 20, 34, 30, 12), .Label = c("104", "109", "115", 
	"13", "139", "145", "15", "16", "176", "1787", "201", "23", "24", 
	"244", "253", "27", "29", "324", "348", "35", "353", "36", "403", 
	"41", "428", "49", "6", "63", "65", "7", "71", "74", "8", "90", 
	"M"), class = "factor")), class = "data.frame", row.names = c("1", 
	"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
	"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
	"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
	"36", "37", "38", "39"))
"census1"<-
structure(.Data = list(income = c(11.652, 23.015, 5.604, 6.71, 7.293, 
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	21.387, 21.771, 17.389, 21.336, 31.825, 12.825, 9.196, 34.561, 
	9.266, 17.692, 12.458, 12.003, 13.624, 27.267, 10.292, 18.353, 
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	28.211, 8.674, 14.337, 35.144, 9.084, 11.651, 12.478, 
	36.002000000000004, 75.361, 20.586, 21.328, 25.522, 10.785, 10.229,
	12.484, 10.832, 51.117, 15.775, 20.417, 23.28, 12.475, 10.745, 
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	22.199, 23.439, 18.728, 15.643, 29.144, 13.708, 17.355, 8.956, 
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	21.728, 13.422, 16.343, 8.346, 14.424, 23.796, 13.255, 8.966, 
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	27.457, 11.317, 16.158000000000002, 10.609, 12.021, 9.041, 20.993, 
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	12.588, 9.598, 25.557, 21.373, 13.173, 33.287999999999996, 6.092, 
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	31.434, 32.473999999999996, 9.288, 33.924, 20.401, 
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	12.242, 38.001, 36.555, 24.934, 14.77, 11.705, 13.089, 19.959, 
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	22.864, 15.325, 12.001, 28.384, 13.901, 6.889, 6.941, 
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	24.401, 17.108, 11.627, 17.128, 17.841000000000002, 10.798, 
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	12.324, 12.169, 36.926, 15.124, 19.757, 29.157, 7.589, 18.251, 
	17.073, 17.383, 13.784, 30.808, 12.997, 15.829, 7.078, 10.094, 
	52.248, 31.42, 28.336, 8.238, 23.127, 11.992, 15.63, 7.599, 37.722,
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	19.547, 30.881, 8.646, 9.4309999999999984, 8.166, 42.341, 52.299, 
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	10.989, 7.899, 20.872, 17.652999999999998, 22.433, 11.81, 13.357, 
	15.464, 6.259, 10.342, 74.799, 10.935, 8.766, 13.466, 7.756, 
	28.122, 24.583, 25.585, 15.115, 19.836, 21.898, 14.976, 5.547, 
	14.497, 20.833, 28.465, 14.819, 14.139, 13.238, 14.346, 23.662, 
	9.4629999999999984, 9.009, 26.823, 18.39, 11.054, 12.617, 
	16.100000000000002, 44.664, 16.425, 15.556, 13.318, 13.149, 21.32, 
	15.944, 9.637, 27.932, 17.722999999999998, 23.376, 12.583, 6.747, 
	15.029, 11.513, 10.431, 11.781, 13.441, 7.856, 17.413, 14.054, 
	11.93, 22.058, 9.304, 19.049, 12.31, 17.449000000000002, 11.936, 
	44.615, 27.949, 13.278, 14.074, 8.7870000000000016, 30.399, 14.042,
	5.599, 14.039, 21.133, 3.955, 10.107, 12.253, 27.037, 21.838, 
	16.414000000000002, 19.381, 7.606, 26.29, 25.93, 
	6.9720000000000008, 9.506, 34.284, 42.492, 14.413, 11.826, 19.143, 
	28.205, 13.6, 18.15, 26.229, 34.195999999999996, 8.701, 
	16.888000000000002, 15.663, 16.122, 7.682, 23.712, 17.085, 8.221, 
	14.907, 14.405, 11.832, 21.522, 15.867, 9.196, 27.43, 18.399, 
	26.346, 26.366, 10.243, 14.301, 25.888, 18.115, 13.776, 14.622, 
	13.465, 12.104, 12.737, 19.233, 14.088, 24.336, 24.108, 31.127, 
	35.295, 24.115, 26.121, 28.568, 17.826, 11.361, 13.349, 36.919, 
	14.006, 35.445, 22.866, 18.241, 9.47, 16.456, 15.839, 14.351, 
	5.223, 15.504, 11.486, 12.363, 15.345, 9.5879999999999984, 12.313, 
	19.581, 10.642, 10.508, 23.433, 12.447, 32.914, 11.045, 24.893, 
	38.544, 6.475, 7.821, 9.378, 12.894, 18.019, 19.73, 26.037, 12.034,
	23.384, 33.659, 13.327, 14.489, 29.186, 28.237, 14.23, 19.392, 
	12.776, 31.885, 30.532, 16.227, 20.212, 42.063, 9.142, 13.107, 
	27.12, 17.677, 19.024, 33.058999999999996, 13.763, 17.992, 18.715, 
	12.192, 14.17, 9.432, 18.42, 4.319, 30.896, 16.524999999999998, 
	24.81, 25.208, 14.612, 19.49, 36.161, 23.167, 17.187999999999998, 
	12.609, 9.32, 31.421, 20.13, 16.059000000000002, 26.387, 46.107, 
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	17.114, 14.271, 24.094, 5.522, 22.954, 17.806999999999998, 11.361, 
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	18.935, 22.536, 10.574, 14.372, 14.082, 11.149, 9.578, 13.618, 
	17.364, 24.683, 13.595, 6.876, 23.885, 7.423, 5.424, 15.572, 
	13.416, 18.512, 38.194, 43.168, 18.512, 23.999, 5.439, 16.843, 
	25.855, 6.666, 7.1, 11.609, 13.564, 21.526, 14.625, 
	16.190000000000002, 11.961, 10.561, 2.234, 25.596, 8.282, 8.151, 
	7.711, 9.861, 26.478, 10.401, 18.485, 8.4120000000000016, 25.272, 
	10.93, 13.685, 14.595, 14.067, 12.412, 24.78, 20.099, 11.69, 
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	12.328, 13.441, 14.919, 12.357, 10.94, 35.482999999999996, 8.635, 
	23.913, 8.5079999999999984, 22.935, 20.844, 24.116, 8.296, 9.361, 
	34.557000000000004, 21.695, 16.913, 16.7, 6.854, 14.713, 21.006, 
	23.41, 25.971, 25.952, 7.854, 69.206, 42.357, 15.039, 7.932, 
	11.527, 27.439, 9.6170000000000016, 11.256, 7.677, 7.61, 24.204, 
	12.526, 16.079, 42.164, 23.861, 8.573, 6.1050000000000008, 13.976, 
	17.636, 19.462, 23.287, 11.221, 8.576, 11.058, 27.798, 10.931, 
	18.572, 8.5, 31.713, 23.173, 8.312, 27.249, 23.616, 21.495, 13.821,
	15.286, 13.163, 24.569, 13.59, 20.017, 15.569, 18.179, 27.956, 
	12.954, 14.621, 21.028, 18.536, 6.614, 18.887, 8.606, 14.42, 
	13.927, 15.483, 8.143, 22.936, 25.441, 17.161000000000002, 9.512, 
	26.001, 18.104, 8.218, 16.913, 18.202, 12.284, 17.527999999999998, 
	24.811, 19.126, 76.464, 16.536000000000002, 16.010000000000002, 
	12.936, 12.471, 43.065, 21.616, 17.742, 9.151, 8.635, 
	17.984000000000002, 10.062, 29.259, 11.895, 17.844999999999998, 
	8.797, 15.623, 12.779, 19.758, 15.586, 10.648, 6.312, 15.581, 
	15.23, 22.386, 30.465, 10.453, 11.432, 25.923, 8.321, 10.293, 
	15.101, 8.14, 15.587, 10.61, 28.651, 20.286, 26.143, 12.681, 7.585,
	6.787, 16.242, 11.822, 10.713, 16.954999999999998, 7.929, 19.306, 
	18.493, 14.386, 11.523, 7.803, 12.107, 6.082, 13.846, 10.459, 
	8.896, 14.213, 10.606, 26.093, 21.681, 12.476, 19.099, 
	17.024999999999998, 39.503, 11.539, 11.132, 22.81, 11.35, 15.474, 
	13.639, 17.552, 35.622, 16.425999999999998, 17.998000000000002, 
	17.457999999999998, 13.9, 12.813, 22.298, 17.425999999999998, 
	23.671, 19.604, 12.915, 12.686, 10.87, 27.963, 10.586, 15.236, 
	29.253, 15.598, 13.926, 14.248, 14.429, 10.917, 5.739, 12.681, 
	15.029, 16.803999999999998, 15.439, 13.761, 8.311, 
	17.047999999999998, 19.079, 9.511, 14.432, 25.895, 22.253, 33.211, 
	5.454, 18.362, 5.6130000000000008, 7.676, 36.073, 10.23, 18.567, 
	9.34, 19.176, 21.577, 11.717, 21.51, 27.23, 23.258, 8.824, 18.384, 
	27.326, 18.295, 75.856, 36.249, 15.864, 32.101, 28.367, 17.631, 
	26.108, 37.537, 22.876, 11.58, 10.123, 13.011, 17.887, 26.03, 
	34.78, 26.17, 22.927, 17.738, 36.051, 14.885, 33.570999999999996, 
	32.662, 5.026, 27.729, 65.688, 21.468, 23.364, 28.408, 37.858, 
	37.375, 44.072, 44.229, 34.709000000000004, 20.578, 20.901, 21.725,
	14.41, 20.364, 60.084, 15.84, 25.234, 23.828, 31.064, 
	35.820999999999996, 34.197000000000004, 13.196, 18.197, 31.291, 
	28.472, 24.164, 24.126, 29.135, 33.567999999999996, 41.772, 57.821,
	23.022, 26.662, 21.948, 14.345, 23.786, 24.58, 55.004, 15.563, 
	28.542, 28.985, 26.935, 18.293, 32.188000000000004, 
	34.554000000000004, 31.427, 32.470999999999996, 34.415999999999996,
	36.144, 28.318, 27.23, 9.252, 32.732999999999996, 58.623, 18.521, 
	39.435, 30.368, 14.814, 22.131, 24.518, 20.555, 25.209, 26.698, 
	33.149, 30.859, 11.672, 14.223, 34.903, 47.54, 15.201, 15.027, 
	34.857, 28.388, 31.265, 23.126, 27.643, 21.71, 25.718, 23.623, 
	64.074, 25.791, 16.579, 21.249, 33.113, 33.255000000000004, 22.696,
	31.519, 77.885, 12.243, 30.288, 17.664000000000002, 11.728, 27.182,
	34.865, 26.558, 36.104, 22.542, 19.438, 26.56, 47.506, 21.82, 
	28.854, 11.812, 23.142, 18.508, 13.335, 11.69, 16.018, 18.856, 
	13.55, 17.167000000000002, 13.389, 42.929, 28.371, 28.716, 43.443, 
	52.598, 8.523, 14.416, 15.703, 27.721, 30.874, 26.632, 22.958, 
	18.713, 36.434, 11.586, 25.557, 28.46, 29.571, 13.773, 12.995, 
	20.655, 18.451, 53.219, 27.366, 47.917, 51.502, 18.411, 12.419, 
	32.412999999999996, 22.415, 31.771, 13.505, 26.855, 50.512, 24.244,
	38.479, 28.243, 17.471, 26.111, 28.283, 17.846, 20.544, 14.538, 
	32.011000000000004, 28.413, 7.699, 22.908, 14.413, 23.663, 11.936, 
	23.695, 26.327, 32.564, 7.244, 17.768999999999998, 19.462, 11.438, 
	10.421, 22.99, 15.969, 14.934, 24.064, 19.424, 41.865, 24.942, 
	27.289, 20.621, 19.095, 19.471, 17.075, 12.123, 18.552, 9.308, 
	12.324, 27.26, 43.456, 23.102, 15.475, 19.641, 31.601, 
	33.517000000000004, 20.437, 32.522, 20.853, 16.163, 218.758, 
	11.563, 19.149, 16.405999999999998, 26.751, 14.092, 27.58, 14.407, 
	31.552, 28.179, 13.674, 18.236, 19.397, 11.564, 22.912, 8.934, 
	19.457, 25.78, 15.54, 26.264, 24.501, 12.326, 14.561, 15.102, 
	13.863, 15.233, 10.832, 32.658, 19.068, 26.271, 16.872, 34.101, 
	17.355, 23.576, 11.846, 17.699000000000002, 35.445, 13.524, 35.762,
	54.919, 35.328000000000004, 15.942, 19.482, 31.639, 19.954, 38.717,
	15.775, 34.057000000000004, 29.263, 41.884, 16.672999999999998, 
	101.677, 36.157, 34.235, 15.85, 13.086, 33.712000000000004, 14.455,
	10.843, 33.317999999999996, 123.174, 18.362, 18.852, 23.235, 
	33.161, 26.141, 33.555, 19.298, 17.536000000000002, 17.163, 11.6, 
	6.2220000000000008, 14.569, 15.982, 38.584, 26.528, 10.822, 4.797, 
	7.182, 62.508, 35.088, 18.335, 23.523, 20.252, 28.255, 22.87, 
	12.919, 22.921, 18.949, 18.444, 15.738, 18.097, 23.059, 26.142, 
	53.397, 6.837, 17.75, 24.13, 20.988, 20.919, 105.587, 27.611, 
	8.438, 13.08, 64.004999999999992, 12.405, 39.823, 22.744, 24.677, 
	19.751, 23.825, 16.761, 12.118, 29.219, 35.585, 16.896, 18.341, 
	16.754000000000002, 17.001000000000002, 22.181, 17.157, 14.904, 
	35.991999999999996, 35.200000000000004, 23.755, 7.776, 37.274, 
	13.23, 25.244, 7.112, 20.815, 15.464, 25.838, 19.587, 14.696, 
	25.799, 7.896, 13.29, 27.848, 24.321, 22.932, 24.139, 20.792, 
	11.881, 26.556, 21.88, 20.734, 28.431, 22.651, 32.154000000000004, 
	31.352, 11.008, 12.217, 9.575, 27.651, 20.011, 30.978, 11.234, 
	29.061, 17.658999999999998, 12.171, 35.793999999999996, 26.466, 
	21.759, 24.128, 82.724, 34.521, 18.48, 31.858, 16.835, 10.531, 
	13.725, 16.401, 14.334, 12.672, 15.146, 38.714, 6.2380000000000008,
	22.206, 12.009, 18.508, 18.475, 17.911000000000002, 6.686, 13.781, 
	24.387, 36.313, 17.326, 19.105, 11.907, 10.507, 12.183, 14.031, 
	21.502, 33.722, 57.347, 22.238, 16.332, 10.759, 19.242, 8.264, 
	15.603, 23.218, 32.455, 14.277, 37.077, 20.875, 21.236, 4.918, 
	17.366, 18.873, 22.22, 15.649, 24.291, 8.789, 11.434, 18.206, 
	42.453, 22.514, 17.433, 29.124, 11.339, 39.807, 12.206, 11.144, 
	15.27, 17.889, 23.21, 18.861, 22.587, 14.241, 22.1, 15.823, 35.729,
	10.637, 20.105, 39.373, 8.206, 22.224, 37.759, 12.123, 45.271, 
	18.625, 26.823, 19.251, 5.336, 14.431, 22.718, 11.431, 28.485, 
	35.165, 41.358, 23.299, 15.622, 43.138, 39.829, 26.532, 23.282, 
	35.988999999999996, 34.353, 43.104, 29.291, 26.601, 9.134, 54.324, 
	32.104999999999996, 38.376, 55.259, 42.702, 13.79, 9.448, 31.883, 
	49.842, 24.157, 7.849, 30.669, 106.69, 18.365, 22.885, 18.333, 
	26.881, 14.929, 21.074, 26.845, 33.295, 43.953, 27.872, 22.559, 
	10.095, 18.486, 7.899, 20.819, 5.805, 22.72, 36.446, 28.719, 8.076,
	21.542, 32.674, 17.204999999999998, 23.589, 7.343, 27.332, 26.135, 
	35.561, 25.59, 6.603, 19.22, 12.531, 28.808, 9.6489999999999984, 
	15.065, 17.05, 18.44, 9.595, 12.747, 16.549, 18.268, 15.94, 23.394,
	15.671, 9.123, 30.547, 14.559, 17.738, 24.169, 17.68, 15.579, 
	18.244, 20.956, 14.422, 13.2, 12.281, 17.129000000000002, 28.748, 
	15.779, 19.247, 12.704, 16.417000000000002, 9.357, 19.813, 18.738, 
	9.555, 17.398, 18.421, 39.468, 9.78, 17.949000000000002, 15.035, 
	7.793, 9.637, 12.409, 9.0850000000000016, 14.301, 41.282, 36.492, 
	34.325000000000004, 12.641, 9.5719999999999984, 8.839, 18.018, 
	15.581, 14.962, 11.685, 3.942, 13.215, 33.704, 13.072, 17.947, 
	19.457, 14.926, 19.544, 36.124, 14.759, 10.824, 14.187, 12.263, 
	9.551, 26.637, 12.139, 14.476, 16.037, 9.357, 11.602, 12.147, 
	10.422, 36.623, 17.396999999999998, 44.046, 39.481, 19.608, 24.707,
	20.605, 23.241, 10.782, 12.417, 20.879, 11.892, 16.268999999999998,
	12.852, 8.61, 19.059, 38.15, 14.448, 8.643, 26.33, 31.514, 12.372, 
	32.097, 20.295, 19.293, 22.362, 17.666, 11.461, 22.128, 16.907, 
	15.936, 17.797999999999998, 15.559, 12.665, 24.524, 7.58, 24.288, 
	8.467, 15.412, 21.185, 11.898, 13.232, 46.395, 8.249, 20.133, 
	37.053, 15.104, 23.889, 23.606, 32.18, 24.264, 18.518, 
	17.260000000000002, 10.713, 33.499000000000004, 5.179, 22.385, 
	10.572, 51.079, 35.932000000000004, 15.853, 21.119, 24.2, 15.628, 
	30.509, 15.729, 19.18, 18.153, 13.774, 22.664, 15.818, 
	16.815000000000002, 28.255, 25.119, 19.822, 17.088999999999998, 
	24.239, 15.788, 10.232, 17.454999999999998, 47.661, 20.413, 27.576,
	33.984, 12.417, 19.548, 44.963, 75.974, 18.789, 25.015, 21.113, 
	15.952, 14.531, 15.797, 32.192999999999996, 10.599, 8.55, 25.886, 
	22.653, 4.628, 14.597, 11.57, 15.562, 12.71, 24.094, 12.685, 
	19.819, 11.551, 27.511, 32.577, 13.943, 32.478, 22.914, 37.637, 
	17.683, 16.892, 26.347, 10.853, 24.362, 15.957, 14.396, 29.635, 
	13.811, 21.345, 44.151, 6.183, 15.856, 26.134, 44.139, 22.877, 
	14.146, 47.317, 15.562, 14.251, 16.942, 23.944, 51.911, 
	32.598999999999996, 12.146, 55.546, 23.343, 23.603, 27.691, 44.127,
	21.791, 28.148, 16.486999999999998, 22.079, 18.44, 39.17, 24.079, 
	15.065, 35.107999999999996, 36.726, 11.998, 21.875, 8.473, 27.182, 
	16.585999999999998, 40.1, 20.551, 69.291, 36.068, 26.643, 25.794, 
	34.348999999999996, 26.451, 47.627, 28.256, 41.228, 34.817, 27.839,
	17.343, 36.059, 8.128, 24.879, 98.423, 10.198, 24.489, 41.826, 
	42.191, 35.982, 3.836, 27.028, 16.697, 45.407, 17.758, 14.169, 
	27.22, 22.764, 18.244, 17.815999999999998, 28.081, 26.126, 33.223, 
	49.473, 0.628, 25.894, 6.908, 30.315, 16.908999999999998, 24.085, 
	13.127, 15.368, 23.621, 19.472, 24.139, 14.031, 24.626, 14.311, 
	18.441, 46.236, 15.924, 19.343, 9.749, 16.663, 33.340000000000004, 
	17.838999999999998, 25.6, 27.806, 15.413, 19.395, 22.562, 18.862, 
	15.601, 21.652, 34.549, 14.406, 31.823, 21.759, 36.115, 24.718, 
	15.579, 14.276, 21.772, 7.521, 23.848, 7.548, 9.876, 25.216, 
	16.161000000000002, 11.272, 17.247, 23.551, 21.668, 33.097, 18.328,
	11.707, 17.873000000000002, 29.3, 22.665, 24.716, 17.349, 26.838, 
	15.211, 8.487, 21.845, 16.488, 20.659, 21.654, 25.852, 13.998, 
	18.476, 14.999, 10.306, 16.924, 20.521, 25.987, 19.155, 26.356, 
	32.182000000000004, 18.246, 31.465, 31.401, 23.883, 44.314, 24.275,
	25.559, 16.024, 13.803, 40.479, 35.101, 28.622, 9.587, 29.289, 
	18.711, 32.631999999999996, 15.953, 6.444, 42.508, 10.586, 14.045, 
	18.505, 13.929, 11.88, 24.512, 26.767, 55.252, 12.348, 34.9, 5.212,
	26.187, 26.469, 13.378, 21.655, 16.386, 25.926, 19.779, 36.154, 
	18.501, 15.214, 32.11, 21.847, 32.393, 15.403, 19.148, 19.473, 
	13.419, 29.401, 44.216, 10.601, 13.864, 26.359, 17.849, 24.253, 
	23.675, 5.352, 10.587, 37.093, 13.201, 22.51, 26.294, 19.552, 
	16.398, 14.948, 27.604, 18.524, 24.883, 12.019, 8.273, 13.479, 
	14.186, 28.358, 9.604, 14.956, 8.8, 19.361, 27.575, 33.418, 13.873,
	17.125, 17.687999999999998, 12.625, 22.82, 40.736, 23.404, 13.973, 
	11.034, 19.306, 7.201, 24.015, 14.203, 13.104, 21.091, 
	33.255000000000004, 17.925999999999998, 23.58, 11.423, 8.232, 
	13.492, 11.74, 26.257, 10.525, 16.494, 30.262, 29.158, 30.977, 
	11.145, 14.466, 15.409, 18.762, 18.598, 18.941, 16.454, 33.42, 
	46.695, 21.262, 59.701, 43.979, 18.848, 27.763, 14.947, 27.988, 
	17.428999999999998, 14.156, 11.328, 17.329, 18.485, 27.126, 15.434,
	14.86, 32.336, 15.616, 16.062000000000002, 42.126, 28.285, 15.934, 
	6.7619999999999992, 35.542, 12.199, 21.189, 11.471, 21.79, 14.916, 
	26.408, 40.207, 15.632, 7.834, 42.395, 15.537, 18.358, 18.448, 
	20.357, 20.638, 41.459, 6.923, 22.987, 24.75, 16.922999999999998, 
	23.688, 12.141, 22.469, 34.860999999999996, 25.65, 10.837, 
	16.469000000000002, 10.581, 11.616, 15.683, 18.095, 14.353, 12.122,
	22.895, 35.278, 12.804, 16.665, 14.606, 17.742999999999998, 22.141,
	12.588, 15.474, 5.058, 25.123, 13.329, 25.622, 25.845, 26.406, 
	24.115, 17.876000000000002, 21.596, 18.708, 22.114, 12.765, 23.449,
	27.501, 38.228, 21.12, 26.989, 11.516, 30.561, 18.801, 38.921, 
	38.748, 29.493, 15.446, 24.478, 23.134, 18.449, 23.334, 7.871, 
	21.271, 14.251, 24.42, 38.152, 22.181, 39.8, 25.974, 28.414, 
	35.959000000000004, 5.604, 18.444, 19.401, 35.737, 23.367, 21.744, 
	31.226, 18.949, 26.759, 16.794, 4.127, 16.572, 18.266, 44.746, 
	28.637, 36.196, 46.015, 42.268, 23.709, 18.073, 25.82, 7.717, 
	11.292, 26.377, 11.336, 18.065, 18.368, 22.474, 10.798, 15.647, 
	4.545, 13.182, 16.577000000000002, 28.667, 27.883, 13.623, 26.309, 
	51.199, 18.344, 15.367, 40.792, 18.539, 21.72, 10.859, 16.962, 
	13.985, 11.525, 9.409, 30.757, 32.269, 25.702, 12.638, 
	17.693000000000002, 31.631, 16.532, 16.241, 16.364999999999998, 
	14.243, 18.113, 15.557, 26.584, 24.735, 14.514, 27.574, 23.602, 
	18.135, 35.953000000000004, 22.983, 31.657, 10.962, 10.371, 8.083, 
	33.331000000000004, 6.758, 12.95, 12.349, 11.48, 10.557, 19.497, 
	50.421, 11.792, 42.32, 23.527, 15.887, 22.396, 32.218000000000004, 
	27.583, 38.027, 22.935, 14.665, 14.035, 17.712, 13.613, 18.149, 
	27.328, 35.787, 25.735, 42.152, 22.593, 7.307, 12.805, 14.561, 
	31.11, 51.727, 26.037, 29.442, 42.635, 11.136, 17.735, 20.128, 
	15.666, 11.806, 31.036, 47.619, 23.998, 21.803, 23.384, 38.236, 
	16.48, 7.311, 16.617999999999998, 22.362, 14.076, 15.552, 14.905, 
	14.204, 14.403, 10.896, 23.396, 58.094, 14.219, 42.098, 21.633, 
	8.637, 6.428, 17.925999999999998, 17.317, 13.347, 55.498, 31.165, 
	12.929, 25.937, 24.479, 10.603, 15.593, 10.397, 10.946, 30.152, 
	33.441000000000004, 21.358, 11.754, 24.493, 14.408, 21.567, 20.633,
	15.586, 25.413, 27.018, 30.67, 18.286, 19.698, 17.690999999999998, 
	13.743, 17.2, 9.251, 16.181, 37.669, 12.018, 11.285, 21.35, 34.229,
	12.621, 15.394, 45.46, 22.527, 26.936, 23.687, 18.941, 22.364, 
	16.364, 24.43, 32.086, 10.694, 33.000999999999996, 18.229, 9.441, 
	12.545, 34.668, 44.871, 33.549, 32.109, 13.403, 34.060000000000004,
	17.25, 8.602, 21.202, 14.783, 10.176, 22.551, 19.544, 17.067, 
	13.665, 11.539, 14.579, 14.532, 7.755, 23.917, 25.166, 41.014, 
	26.048, 32.340000000000004, 17.741, 18.587, 24.314, 19.507, 8.526, 
	14.79, 34.134, 18.923, 35.566000000000004, 40.135, 
	35.756999999999996, 19.389, 15.735, 8.409, 13.277, 12.395, 6.567, 
	10.493, 7.678, 22.448, 11.326, 44.046, 18.502, 10.843, 27.234, 
	15.973, 7.337, 7.168, 11.568, 10.578, 22.623, 27.899, 11.643, 
	15.516, 18.337, 17.172, 7.111, 10.513, 21.153, 18.495, 15.397, 
	12.603, 10.35, 8.001, 17.681999999999998, 13.836, 14.158, 10.935, 
	9.312, 9.294, 16.965, 17.841999999999998, 25.55, 8.84, 14.41, 
	13.298, 14.17, 17.227, 10.911, 16.372, 37.716, 9.405, 14.453, 
	12.753, 11.938, 13.369, 46.497, 13.893, 12.477, 10.441, 15.388, 
	24.427, 31.911, 10.614, 44.538, 14.422, 35.334000000000004, 
	35.587000000000004, 28.01, 29.573, 14.184, 10.092, 19.696, 16.122, 
	40.501, 26.552, 16.991, 32.051, 27.479, 16.312999999999998, 18.54, 
	11.963, 8.337, 9.59, 7.074, 13.064, 14.059, 25.123, 12.124, 22.98, 
	12.309, 15.519, 22.061, 24.17, 8.78, 18.015, 7.574, 26.953, 42.688,
	21.435, 22.503, 21.026, 32.008000000000004, 15.075, 39.215, 11.522,
	28.481, 13.855, 21.103, 10.673, 8.0850000000000016, 61.167, 27.237,
	25.245, 28.712, 28.566, 16.542000000000002, 40.022, 19.305, 16.326,
	10.855, 10.282, 23.593, 22.028, 15.566, 5.579, 36.343, 11.332, 
	22.568, 20.806, 7.531, 14.741, 7.812, 17.065999999999998, 
	16.577000000000002, 7.534, 27.952, 17.695, 36.771, 12.702, 7.933, 
	6.425, 35.851, 16.146999999999998, 13.069, 21.325, 32.301, 23.024, 
	19.694, 12.199, 18.242, 8.504, 12.514, 23.055, 15.525, 28.136, 
	23.707, 20.807, 34.298, 45.68, 8.77, 14.438, 15.261, 13.129, 
	11.957, 7.931, 17.123999999999998, 13.549, 26.11, 13.669, 
	6.1050000000000008, 12.663, 38.334, 9.265, 44.002, 24.617, 8.495, 
	11.595, 15.497, 42.934, 15.187, 23.264, 18.317, 12.103, 0.518, 
	45.654, 7.839, 12.283, 33.418, 17.934000000000002, 19.307, 7.281, 
	17.905000000000002, 12.621, 12.401, 36.795, 10.408, 25.558, 13.869,
	12.578, 24.42, 17.326, 19.428, 32.186, 6.107, 11.426, 32.275, 
	23.223, 11.979, 28.456, 20.943, 19.39, 32.256, 8.733, 18.115, 
	19.511, 14.217, 12.643, 13.998, 13.086, 22.463, 54.164, 28.609, 
	9.984, 21.799, 9.8989999999999984, 14.093, 18.493, 14.59, 
	6.2140000000000008, 28.696, 21.176, 6.568, 12.028, 14.304, 5.984, 
	27.295, 8.674, 7.754, 9.244, 37.088, 15.572, 21.661, 19.089, 
	26.533, 12.404, 16.765999999999998, 9.234, 12.906, 7.904, 14.354, 
	27.534, 41.075, 17.547, 22.734, 11.045, 4.164, 43.321, 18.288, 
	14.386, 23.864, 7.628, 10.28, 15.304, 13.974, 27.477, 14.435, 
	7.919, 12.174, 6.049, 16.844999999999998, 12.471, 21.282, 8.471, 
	28.034, 12.224, 9.405, 24.487, 22.826, 18.109, 18.73, 23.533, 
	12.874, 33.135, 9.169, 10.719, 13.544, 6.298, 27.068, 22.58, 
	11.688, 9.636, 11.754, 7.277, 14.03, 13.267, 14.037, 15.561, 
	18.163, 18.407, 30.8, 15.543, 11.51, 7.44, 10.409, 14.44, 8.948, 
	17.058, 11.527, 12.552, 2.531, 10.15, 18.236, 11.41, 14.295, 
	15.577, 13.545, 13.636, 13.963, 12.788, 15.971, 9.229, 11.503, 
	13.68, 42.171, 6.293, 5.702, 16.745999999999998, 15.82, 16.087, 
	15.844, 11.585, 18.557, 36.965, 7.851, 16.177, 23.898, 10.657, 
	9.4280000000000016, 14.682, 14.177, 7.943, 10.508, 20.783, 18.478, 
	10.261, 28.827, 17.890999999999998, 11.375, 11.687, 18.471, 14.474,
	14.443, 14.216, 23.679, 17.015999999999998, 17.359000000000002, 
	10.771, 15.8, 35.941000000000004, 10.443, 12.319, 13.67, 23.33, 
	26.491, 24.218, 28.903, 15.467, 13.109, 12.164, 31.703, 9.279, 
	7.048, 27.217, 7.716, 10.579, 11.323, 14.883, 18.514, 13.419, 
	17.928999999999998, 18.213, 13.483, 17.361999999999998, 25.094, 
	10.853, 7.565, 5.745, 15.226, 12.886, 6.243, 12.042, 8.903, 26.78, 
	18.203, 83.762, 7.759, 15.681, 15.208, 21.697, 23.605, 10.876, 
	12.154, 6.471, 14.031, 15.703, 9.638, 11.102, 21.613, 26.657, 
	16.829, 14.192, 11.509, 22.173, 10.282, 10.748, 28.542, 13.719, 
	23.481, 11.821, 12.484, 18.946, 29.709, 27.336, 14.084, 8.99, 
	13.034, 5.967, 10.429, 9.255, 9.753, 7.841, 6.508, 10.452, 14.082, 
	9.345, 16.126000000000002, 13.673, 18.295, 14.864, 11.407, 14.5, 
	11.256, 17.34, 12.492, 15.079, 26.092, 12.597, 6.167, 10.471, 
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	11.285, 8.885, 15.142, 14.092, 164.082, 10.847, 10.532, 8.579, 
	8.918, 4.701, 8.355, 11.151, 7.28, 15.555, 15.397, 22.891, 
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	11.678, 9.229, 24.437, 25.873, 8.825, 12.438, 17.315000000000002, 
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"census2"<-
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"census3"<-
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	4.0425, 3.9255, 4.12, 4.0865, 4.0991, 4.1722, 4.191, 4.5289, 4.1593, 
	4.0798, 4.2633, 4.273, 4.5893, 4.1925, 4.2469, 4.2302, 3.9711, 4.1492, 
	4.1637, 4.659, 4.2479, 4.282, 4.1378, 4.2281, 4.4365, 4.3376, 4.2432, 
	4.1953, 4.3057, 4.1101, 4.3817, 4.0161, 3.7555, 3.9533, 4.1075, 4.5409, 
	4.3615, 3.862, 3.9756, 4.2864, 4.3886, 4.0678, 4.1918, 4.0632, 4.2894, 
	4.108, 4.0613, 4.3483, 4.398, 4.2411, 4.5136, 4.5089, 4.0797, 4.1588, 
	4.1163, 4.1746, 3.8081, 4.2476, 4.1123, 4.5286, 4.2828, 4.437, 3.8964, 
	4.1911, 4.4899, 4.0399, 3.8874, 4.2911, 4.0909, 3.6654, 4.6465, 3.7638, 
	3.9603, 4.1207, 4.5, 4.2265, 4.1216, 4.432, 4.4582, 4.149, 4.2176, 
	4.4439, 4.5199, 3.8804, 4.1733, 4.0869, 4.4145, 4.3583, 4.2574, 4.2252, 
	4.5054, 4.3385, 4.3613, 4.0865, 3.8904, 4.2093, 4.2262, 3.8802, 3.9772, 
	4.3466, 4.2631, 4.0628, 4.2244, 4.3933, 4.2415, 4.1545, 4.106, 4.2432, 
	4.149, 4.118, 4.2756, 4.7438, 4.249, 4.0951, 4.5206, 4.1538, 4.212, 
	4.2537, 4.2748, 4.2448, 4.2584, 4.2255, 3.6872, 4.8835, 4.0758, 4.4238, 
	3.9231, 4.0029, 4.1279, 4.2378, 4.3628, 4.3452, 4.239, 4.1613, 4.2674, 
	4.6629, 3.8069, 3.9115, 4.1203, 4.4006, 3.9443, 4.3127, 3.9679, 4.0678, 
	4.5223, 3.7424, 4.1925, 4.7103, 4.0853, 3.7999, 4.2828, 3.2071, 4.3326, 
	3.8624, 4.7423, 4.6779, 3.1989, 4.4393, 4.2403, 4.2444, 3.7363, 3.9146, 
	3.9898, 4.3376, 4.4606, 4.5622, 4.2556, 4.4283, 4.4, 4.2145, 4.3868, 
	4.1053, 4.3022, 4.3832, 4.2377, 4.1948, 4.1694, 4.0499, 4.2526, 4.3106, 
	4.2762, 4.3127, 4.3492, 4.318, 4.4269, 4.5, 4.2987, 4.2784, 4.3678, 
	4.2111, 3.9926, 4.0707, 4.2714, 4.2261, 4.0401, 4.0145, 4.3119, 4.3976, 
	4.5871, 4.1714, 4.3099, 4.3816, 4.235, 4.352, 4.162, 4.5142, 4.1064, 
	4.074, 4.4673, 4.0905, 4.3268, 4.3024, 4.3607, 4.1579, 4.0222, 4.1973, 
	4.1443, 4.0551, 3.8558, 3.9024, 4.2306, 3.8743, 4.3158, 4.1681, 4.0887, 
	4.4571, 3.9345, 4.2483, 4.1477, 4.2124, 4.3385, 4.2562, 3.8685, 4.1165, 
	4.2755, 4.3016, 4.5741, 4.0704, 4.2638, 3.9598, 4.2214, 3.9682, 3.9912, 
	4.4728, 4.2134, 3.9384, 4.2031, 4.3854, 4.4272, 4.4758, 4.3909, 3.9148, 
	4.5362, 4.5773, 4.4973, 4.2452, 4.4341, 4.1759, 4.2532, 4.2468, 4.2676, 
	4.0935, 4.4519, 4.2254, 3.9486, 4.4265, 4.2436, 4.2235, 4.3782, 4.1625, 
	4.3735, 3.7908, 4.1962, 4.2874, 4.4173, 4.1299, 4.0551, 4.3786, 3.965, 
	4.3554, 3.9788, 4.1875, 4.11, 4.0514, 3.984, 4.1032, 4.1356, 4.36, 
	4.1196, 4.2681, 4.3909, 4.2386, 4.0601, 4.4114, 4.265, 4.183, 4.3871, 
	4.2192, 4.2079, 4.1989, 3.8544, 4.3242, 4.1117, 4.131, 4.2282, 4.1275, 
	4.1987, 4.2048, 4.3196, 4.5113, 4.1193, 4.1454, 4.0278, 4.3205, 4.3599, 
	4.0437, 4.2649, 4.0892, 3.8781, 4.2052, 4.0405, 4.3632, 4.2768, 4.3036, 
	4.3307, 4.2002, 4.1301, 4.3864, 4.2413, 4.4219, 4.2239, 4.0498, 4.0532, 
	4.1619, 4.163, 4.3089, 4.198, 4.1746, 4.1335, 4.5097, 4.172, 4.3372, 
	4.2329, 4.2598, 4.242, 4.2853, 4.2498, 3.963, 4.1829, 4.354, 4.2002, 
	4.4651, 3.8592, 4.2605, 4.1285, 4.0179, 4.1323, 4.4514, 3.9426, 3.745, 
	4.0975, 4.7101, 3.8191, 4.2423, 3.8255, 4.1637, 4.5114, 4.342, 4.2531, 
	4.3238, 4.3525, 4.2641, 4.3438, 4.382, 4.106, 4.3869, 4.4239, 4.2921, 
	4.1152, 4.5084, 4.13, 4.4287, 3.9164, 4.334, 4.1426, 4.3665, 4.0412, 
	4.2631, 4.2584, 4.1004, 4.3766, 4.1551, 4.1202, 4.2006, 4.1977, 4.1191, 
	4.1327, 4.2952, 4.1619, 4.1328, 4.2671, 4.1176, 4.463, 4.1047, 4.1514, 
	4.2035, 4.2325, 4.4344, 4.1773, 4.2172, 4.4631, 4.5066, 4.3395, 4.0833, 
	4.1881, 4.3325, 4.0756, 4.2226, 4.0281, 4.1984, 4.2862, 4.0987, 4.1314, 
	4.2723, 4.2341, 4.2826, 4.386, 4.1741, 4.2338, 4.1972, 4.3494, 4.4365, 
	4.1406, 4.1933, 4.3082, 4.2871, 4.2744, 4.1777, 4.7097, 4.1439, 4.4543, 
	4.3021, 4.4803, 4.0314, 4.1634, 4.3199, 4.4387, 4.1652, 4.2944, 4.2284, 
	4.3619, 3.9709, 4.2346, 4.2968, 4.2183, 4.0063, 4.1452, 4.4002, 4.3208, 
	4.0729, 3.9779, 4.4362, 4.0089, 4.2888, 4.1943, 4.4853, 4.3239, 4.1283, 
	4.1172, 4.2924, 4.1467, 3.9707, 4.1981, 4.2162, 4.4584, 4.1973, 4.3072, 
	4.0743, 4.222, 4.2398, 4.2483, 4.1618, 4.2392, 4.2582, 4.4654, 4.2704, 
	4.3, 3.967, 4.3376, 4.1728, 4.2421, 4.086, 4.0218, 4.3099, 4.2523, 
	4.1911, 4.3562, 4.284, 4.4031, 4.154, 4.0871, 4.3433, 4.0398, 4.3737, 
	4.2956, 4.2124, 4.2177, 4.313, 4.0619, 4.1424, 3.9953, 4.2984, 4.3873, 
	4.0279, 4.1172, 4.1973, 4.4527, 4.4096, 4.051, 4.297, 4.264, 4.1948, 
	4.2194, 4.274, 4.2608, 4.1013, 4.3155, 4.0135, 4.1794, 4.1782, 4.4474, 
	4.3194, 3.9203, 4.3465, 4.1758, 4.0718, 3.9989, 4.2348, 4.2495, 4.166, 
	4.663, 4.3989, 4.0758, 4.3435, 4.1737, 4.0191, 4.2081, 4.3029, 3.9833, 
	4.2444, 3.8947, 4.2814, 4.235, 4.3255, 4.2776, 4.0317, 4.1855, 3.9851, 
	4.3765, 4.466, 4.1217, 4.127, 4.2737, 4.1295, 4.1321, 4.0585, 4.3409, 
	3.8316, 4.2788, 4.3759, 4.1404, 4.1357, 4.187, 4.2203, 4.3177, 4.341, 
	4.0315, 4.2519, 4.3622, 4.346, 4.3055, 4.3212, 4.3788, 4.4321, 4.3705, 
	4.2192, 4.1596, 4.223, 4.4031, 4.3321, 4.1146, 4.3075, 4.1614, 4.2162, 
	4.1805, 4.3059, 4.1494, 4.2683, 4.0571, 4.2294, 4.2226, 4.3004, 4.3126, 
	4.2933, 4.2762, 4.3706, 4.1259, 4.1627, 4.2914, 4.3522, 4.37, 4.1515, 
	4.175, 4.2136, 4.4108, 4.3382, 4.2665, 4.1134, 4.1466, 4.0883, 4.3762, 
	4.2798, 4.2325, 4.4861, 4.0559, 4.2376, 4.3464, 4.2962, 4.3131, 4.6096, 
	4.2489, 4.4092, 4.3478, 4.2447, 4.1755, 3.9456, 4.103, 4.1769, 4.1363, 
	4.3764, 4.0986, 4.2055, 4.2012, 4.0927, 4.2248, 4.2453, 4.2295, 4.3449, 
	4.2761, 4.2474, 4.2958, 4.1723, 4.2159, 4.2944, 4.3506, 4.0893, 4.2977, 
	4.3304, 4.2805, 4.2424, 4.2049, 4.2964, 4.1781, 4.1189, 4.1671, 4.0224, 
	4.1126, 4.2221, 4.3531, 4.2963, 4.4097, 4.2045, 4.5695, 4.2102, 4.2967, 
	4.0682, 4.2668, 4.0368, 4.2292, 4.0194, 4.4485, 4.161, 4.2426, 4.2333, 
	4.119, 4.0341, 4.2856, 4.3034, 4.0819, 4.4373, 4.2695, 4.2624, 3.9432, 
	4.3827, 4.2016, 4.1976, 4.3087, 4.3938, 4.145, 4.2048, 4.3482, 4.2997, 
	4.2036, 4.2598, 4.3563, 4.2889, 4.299, 4.5758, 4.1712, 4.183, 4.2915, 
	4.0401, 4.1725, 4.4565, 4.1892, 4.2277, 4.2682, 4.1889, 4.2814, 4.2473, 
	4.347, 4.181, 4.0535, 4.3292, 4.1932, 4.3892, 4.4182, 4.0376, 4.1707, 
	4.1099, 4.4757, 4.2726, 4.2274, 4.1785, 4.4398, 4.1705, 4.2855, 4.1078, 
	4.239, 4.3345, 4.2459, 4.4663, 4.3081, 3.9702, 4.1287, 3.987, 4.1334, 
	4.1075, 4.1887, 4.2919, 4.0408, 4.2977, 4.2544, 4.2587, 4.4917, 4.3932, 
	4.3046, 3.9765, 4.1466, 4.2134, 4.2452, 4.1698, 4.1727, 4.3084, 4.3595, 
	4.3331, 4.2268, 4.1815, 4.1612, 4.2467, 4.0398, 4.3163, 4.3255, 4.1082, 
	4.0645, 4.1837, 4.2857, 3.9857, 4.3684, 4.398, 4.2305, 4.0835, 4.2623, 
	4.2197, 4.1201, 4.0319, 4.3536, 4.337, 4.0401, 4.3327, 4.1595, 4.2176, 
	4.1793, 4.1471, 4.2102, 4.2704, 4.1649, 4.3998, 4.0354, 4.217, 4.4797, 
	4.2741, 4.3017, 4.227, 4.0252, 4.1445, 4.3058, 4.3628, 4.4405, 4.3932, 
	4.4569, 4.3453, 4.2866, 4.212, 4.2662, 4.1996, 4.0855, 4.1854, 4.1145, 
	4.1508, 4.2209, 4.4109, 4.2509, 4.2455, 4.1459, 4.255, 4.0977, 4.2511, 
	4.1175, 4.2257, 4.2251, 4.1636, 4.2796, 4.1017, 4.1333, 4.3843, 4.2244, 
	4.4356, 4.3164, 4.0505, 4.0714, 4.2712, 4.0302, 4.2547, 4.3802, 4.3873, 
	4.2302, 4.1862, 4.2128, 4.2199, 4.3346, 4.102, 4.1928, 4.2602, 4.3202, 
	4.3037, 4.2666, 4.3407, 3.9621, 4.2598, 4.2268, 4.1559, 4.3443, 4.1648, 
	4.1827, 4.2412, 4.244, 4.2963, 4.1836, 4.1543, 4.2325, 4.2725, 4.1226, 
	4.0836, 4.3074, 4.1419, 4.3841, 4.1693, 4.4589, 4.5522, 4.3392, 4.3882, 
	4.2209, 4.412, 4.176, 4.3612, 4.1762, 4.3745, 3.9279, 4.4676, 4.0462, 
	4.2557, 4.2379, 4.4584, 4.0982, 4.262, 4.3537, 4.0401, 4.2936, 4.2227, 
	4.3311, 4.2243, 4.2693, 4.1751, 4.1019, 4.205, 4.32, 4.2724, 4.2868, 
	4.1499, 4.638, 4.3158, 4.3614, 4.2341, 4.3524, 4.2396, 4.1979, 4.2399, 
	4.2525, 4.1756, 4.2437, 4.2015, 4.3132, 4.0566, 4.1402, 4.0885, 4.1569, 
	4.4159, 4.2018, 4.4589, 4.3568, 4.2688, 4.2351, 4.1618, 4.3315, 4.104, 
	4.2617, 4.2941, 4.2583, 4.3684, 4.1297, 4.1306, 4.212, 4.2104, 4.2083, 
	4.2428, 4.2722, 4.1937, 4.2368, 4.0803, 4.3856, 4.2741, 4.2336, 4.2338, 
	4.0813, 4.2444, 4.265, 4.1564, 4.2011, 4.1254, 4.1888, 4.2321, 4.1817, 
	4.2253, 4.4784, 4.3668, 4.3725, 4.3054, 4.2876, 4.1595, 4.2997, 4.1653, 
	4.3764, 4.3091, 4.3826, 4.1791, 4.3054, 4.2221, 4.2404, 4.2077, 4.154, 
	4.2948, 4.3174, 4.174, 4.3037, 4.2323, 4.3049, 4.2321, 4.1699, 4.2795, 
	4.2739, 4.295, 4.4343, 4.3371, 4.1205, 4.1378, 4.2184, 4.1889, 4.1956, 
	4.2592, 4.2575, 4.2255, 4.2695, 4.2755, 4.2025, 4.2784, 4.108, 4.1492, 
	4.3427, 4.3905, 4.2297, 4.1218, 4.2146, 4.2257, 4.1386, 4.2516, 4.2513, 
	4.1464, 4.2676, 4.3262, 4.1965, 4.284, 4.3266, 4.3853, 4.2018, 4.1415, 
	4.2909, 4.2413, 4.244, 4.2, 4.2852, 4.2617, 4.1849, 4.3176, 4.2641, 
	4.2087, 4.2819, 4.3556, 4.0119, 4.1188, 4.1648, 4.2646, 4.4163, 4.1536, 
	4.2018, 4.1773, 4.3531, 4.2106, 4.179, 4.2568, 4.0868, 4.1644, 4.3662, 
	4.1709, 4.1751, 4.2499, 4.1693, 4.2023, 4.1975, 4.2794, 4.1913, 4.3319, 
	4.1285, 4.2976, 4.4238, 4.3452, 4.2548, 4.1246, 4.1495, 4.3097, 4.2059, 
	4.1922, 4.1967, 4.2079, 4.1714, 4.3403, 4.1729, 4.123, 4.3587, 4.2167, 
	4.2648, 4.1601, 4.3462, 4.2504, 4.1188, 4.2608, 4.1997, 4.2519, 4.1866, 
	4.1995, 4.1818, 4.2527, 4.4865, 4.2973, 4.2949, 4.3051, 4.1801, 4.194, 
	4.2589, 4.226, 4.3026, 4.2338, 4.183, 4.2467, 4.2761, 4.4247, 4.3289, 
	4.1767, 4.198, 4.2766, 4.1474, 4.1958, 4.3151, 4.2935, 4.2056, 4.2557, 
	4.2918, 4.1478, 4.1913, 4.2597, 4.1858, 4.2984, 4.1586, 4.2338, 4.1475, 
	4.2241, 4.3631, 4.3363, 4.2397, 4.2233, 4.2564, 4.2159, 4.2273, 4.2753, 
	4.1893, 4.1175, 4.3655, 4.3807, 4.2677, 4.266, 4.268, 4.3026, 4.231, 
	4.2537, 4.1616, 4.3576, 4.217, 4.23, 4.2155, 4.3087, 4.3566, 4.1971, 
	4.2663, 4.2432, 4.2914, 4.2684, 4.2118, 4.3546, 4.3, 4.0897, 4.2646, 
	4.1599, 4.3385, 4.1167, 4.2604, 4.2513, 4.3015, 4.1438, 4.2018, 4.2222, 
	4.2521, 4.4015, 4.218, 4.2692, 4.1633, 4.3687, 4.3702, 4.2753, 4.2324, 
	4.2667, 4.1954, 4.0771, 4.0693, 4.3331, 4.3267, 4.188, 4.2087, 4.3453, 
	4.1662, 4.0788, 4.173, 4.1852, 4.2552, 4.3831, 4.3164, 4.2463, 4.2049, 
	4.1613, 4.2407, 4.2313, 4.3045, 4.3472, 4.1885, 4.2855, 4.2565, 4.3075, 
	4.3009, 4.2201, 4.1684, 4.4371, 4.2035, 4.204, 4.1343, 4.3342, 4.2873, 
	4.0605, 4.1164, 4.1925, 4.1751, 4.1789, 4.1, 4.2435, 4.3823, 4.3223, 
	4.2778, 4.3531, 4.3068, 4.1514, 4.3828, 4.2646, 4.3716, 4.1208, 4.1783, 
	4.1987, 4.2988, 4.2405, 4.2179, 4.3106, 4.3083, 4.2424, 4.2524, 4.125, 
	4.3001, 4.2355, 4.3276, 4.1405, 4.2785, 4.1711, 4.261, 4.2756, 4.1179, 
	4.1641, 4.2926, 4.1852, 4.1113, 4.2874, 4.225, 4.3146, 4.1643, 4.2439, 
	4.1973, 4.2552, 4.2189, 4.1806, 4.3029, 4.2074, 4.3208, 4.2196, 4.3127, 
	4.2278, 4.2962, 4.1954, 4.2886, 4.0634, 4.271, 4.2358, 4.262, 4.3201, 
	4.2176, 4.2509, 4.273, 4.4164, 4.2783, 4.3531, 4.3674, 4.219, 4.2386, 
	4.2427, 4.253, 4.1802, 4.2266, 4.1241, 4.2435, 4.2802, 4.1439, 4.4057, 
	4.1256, 4.3452, 4.1527, 4.2784, 4.291, 4.2513, 4.3297, 4.3402, 4.1975, 
	4.1899, 4.0824, 4.1691, 4.3231, 4.1723, 4.283, 4.3212, 4.1287, 4.3134, 
	4.3629, 4.2512, 4.2362, 4.3477, 4.2057, 4.2931, 4.1463, 4.2375, 4.1881, 
	4.146, 4.2675, 4.207, 4.2409, 4.1402, 4.2241, 4.1902, 4.2623, 4.2279, 
	4.1994, 4.3159, 4.1674, 4.1438, 4.1401, 4.2644, 4.385, 4.2567, 4.1533, 
	4.2494, 4.2956, 4.2774, 4.2951, 4.2335, 4.2186, 4.2374, 4.107, 4.2077, 
	4.3215, 4.2486, 4.1756, 4.2893, 4.2747, 4.1569, 4.2053, 4.3459, 4.2422, 
	4.2573, 4.2248, 4.279, 4.1972, 4.3577, 4.2454, 4.2268, 4.2674, 4.2524, 
	4.2397, 4.2758, 4.3123, 4.247, 4.1921, 4.2937, 4.2496, 4.2492, 4.2679, 
	4.3131, 4.1951, 4.2059, 4.2364, 4.2465, 4.2589, 4.1465, 4.3442, 4.1755, 
	4.1827, 4.2227, 4.2743, 4.2861, 4.25, 4.2544, 4.2393, 4.231, 4.2826, 
	4.2886, 4.0923, 4.2982, 4.1803, 4.2582, 4.207, 4.2143, 4.1815, 4.2055, 
	4.21, 4.2415, 4.3717, 4.2067, 4.2291, 4.1924, 4.1923, 4.2139, 4.2749, 
	4.2637, 4.1891, 4.2436, 4.182, 4.3409, 4.2899, 4.2187, 4.2452, 4.2365, 
	4.3033, 4.2779, 4.1945, 4.2587, 4.2384, 4.2394, 4.2154, 4.2221, 4.2102, 
	4.3117, 4.2233, 4.2418, 4.2121, 4.3192, 4.2422, 4.2919, 4.2347, 4.2533, 
	4.273, 4.2646, 4.2862, 4.2615, 4.2113, 4.2498, 4.2078, 4.2217, 4.2217, 
	4.2965, 4.2453, 4.3333, 4.2394, 4.0969, 4.2923, 4.2685, 4.1535, 4.1899, 
	4.299, 4.2258, 4.2492, 4.2757, 4.2793, 4.2689, 4.2898, 4.1692, 4.2506, 
	4.1458, 4.1565, 4.2753, 4.3227, 4.2418, 4.3362, 4.191, 4.2454, 4.2612, 
	4.2691, 4.2222, 4.2569, 4.2043, 4.228, 4.2165, 4.1845, 4.2649, 4.2079, 
	4.224, 4.2281, 4.2644, 4.2535, 4.2747, 4.1896, 4.2713, 4.2299, 4.3446, 
	4.303, 4.2652, 4.2197, 4.1913, 4.2637, 4.2565, 4.2172, 4.3041, 4.2404, 
	4.1513, 4.2383, 4.253, 4.3138, 4.2907, 4.2277, 4.2006, 4.198, 4.2027, 
	4.1982, 4.2434, 4.2261, 4.1865, 4.2851, 4.2509, 4.2735, 4.2313, 4.2049, 
	4.2193, 4.2583, 4.2505, 4.2405, 4.2397, 4.2865, 4.2534, 4.1878, 4.1718, 
	4.199, 4.2113, 4.2698, 4.3618, 4.2288, 4.2148, 4.1815, 4.2281, 4.2131, 
	4.2358, 4.272, 4.3049, 4.3444, 4.137, 4.2319, 4.2126, 4.1642, 4.1356, 
	4.2809, 4.2413, 4.2403, 4.2383, 4.2298, 4.3028, 4.1572, 4.2964, 4.1753, 
	4.236, 4.2428, 4.2689, 4.234, 4.2066, 4.1768, 4.233, 4.304, 4.2801, 
	4.2069, 4.2434, 4.2279, 4.2289, 4.2532, 4.2579, 4.2143, 4.1642, 4.1724, 
	4.1964, 4.2941, 4.263, 4.1971, 4.1924, 4.1908, 4.1614, 4.2491, 4.2297, 
	4.1775, 4.2849, 4.2716, 4.1808, 4.2316, 4.1744, 4.2471, 4.3747, 4.1822, 
	4.1662, 4.2242, 4.2819, 4.305, 4.2576, 4.2952, 4.1952, 4.2453, 4.2577, 
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	4.2164, 4.2271, 4.2261, 4.3037, 4.2619, 4.3126, 4.2371, 4.2598, 4.2295, 
	4.2495, 4.2762, 4.1915, 4.2447, 4.2004, 4.2766, 4.177, 4.1737, 4.1822, 
	4.1502, 4.2032, 4.2236, 4.248, 4.2357, 4.2827, 4.1344, 4.2157, 4.3158, 
	4.2033, 4.2513, 4.2263, 4.2045, 4.1834, 4.1798, 4.1693, 4.2535, 4.1916, 
	4.1769, 4.238, 4.1566, 4.2633, 4.1497, 4.2719, 4.3169, 4.2351, 4.2218, 
	4.1926, 4.156, 4.2616, 4.1965, 4.3205, 4.2461, 4.1515, 4.2009, 4.2583, 
	4.2066, 4.1349, 4.2153, 4.3119, 4.2598, 4.3566, 4.2552, 4.21, 4.2505, 
	4.1414, 4.1107, 4.2443, 4.2666, 4.2347, 4.1763, 4.2789, 4.1653, 4.2443, 
	4.2629, 4.2698, 4.2254, 4.3208, 4.2545, 4.343, 4.2674, 4.2525, 4.2555, 
	4.2897, 4.249, 4.2334, 4.1539, 4.2822, 4.3019, 4.2452, 4.2987, 4.2705, 
	4.1915, 4.2413, 4.2419, 4.2719, 4.1762, 4.2197, 4.2335, 4.2348, 4.2209, 
	4.1904, 4.2752, 4.2821, 4.2352, 4.241, 4.1773, 4.2991, 4.2798, 4.2488, 
	4.1493, 4.2111, 4.2474, 4.2735, 4.1905, 4.2275, 4.2461, 4.3095, 4.2272, 
	4.1795, 4.2345, 4.2497, 4.2065, 4.3355, 4.2661, 4.2804, 4.2902, 4.2264, 
	4.2902, 4.2364, 4.1472, 4.2694, 4.2456, 4.2421, 4.1771, 4.2056, 4.2195, 
	4.1868, 4.1979, 4.3687, 4.208, 4.2305, 4.2311, 4.2708, 4.2247, 4.2194, 
	4.213, 4.2319, 4.2204, 4.2679, 4.23, 4.2001, 4.2755, 4.3023, 4.192, 
	4.1929, 4.1911, 4.1696, 4.2793, 4.2427, 4.282, 4.2684, 4.2036, 4.2431, 
	4.2486, 4.1905, 4.1904, 4.2502, 4.1962, 4.2413, 4.2466, 4.2232, 4.1994, 
	4.2689, 4.2003, 4.187, 4.2797, 4.2685, 4.2779, 4.2469, 4.2283, 4.2542, 
	4.2206, 4.2949, 4.2192, 4.2568, 4.2293, 4.2677, 4.2108, 4.2418, 4.205, 
	4.2643, 4.2328, 4.249, 4.2209, 4.2796, 4.3115, 4.2359, 4.2465, 4.2233, 
	4.3234, 4.2052, 4.2185, 4.2234, 4.2621, 4.2144, 4.2972, 4.2748, 4.2354, 
	4.2418, 4.2106, 4.22, 4.2653, 4.2479, 4.2609, 4.2338, 4.1725, 4.2286, 
	4.1981, 4.2584, 4.2242, 4.2576, 4.2723, 4.2332, 4.2999, 4.2237, 4.2265, 
	4.2162, 4.2139, 4.1981, 4.2278, 4.2298, 4.2297, 4.2665, 4.2933, 4.2569, 
	4.2956, 4.2232, 4.231, 4.2205, 4.2503, 4.2119, 4.1792, 4.1962, 4.2621, 
	4.26, 4.2945, 4.2631, 4.2506, 4.1863, 4.235, 4.24, 4.2401, 4.1742, 
	4.2137, 4.2646, 4.2083, 4.2221, 4.2525, 4.229, 4.2312, 4.2098, 4.2692, 
	4.2175, 4.2485, 4.2095, 4.261, 4.2655, 4.2516, 4.2554, 4.219, 4.2165, 
	4.2101, 4.2965, 4.2485, 4.3, 4.2125, 4.2043, 4.2712, 4.2244, 4.3202, 
	4.2312, 4.2222, 4.2175, 4.2064, 4.2207, 4.2668, 4.1896, 4.2187, 4.2692, 
	4.2306, 4.2708, 4.199, 4.2856, 4.2597, 4.2096, 4.2231, 4.2474, 4.2246, 
	4.2383, 4.246, 4.2374, 4.2083, 4.2532, 4.2077, 4.2484, 4.2197, 4.2578, 
	4.2001, 4.1743, 4.2698, 4.2181, 4.2216, 4.2787, 4.2569, 4.239, 4.2769, 
	4.237, 4.1661, 4.2863, 4.1676, 4.2218, 4.255, 4.2439, 4.236, 4.2424, 
	4.2139, 4.2387, 4.2547, 4.1958, 4.2317, 4.196, 4.2186, 4.197, 4.2136, 
	4.2518, 4.2057, 4.245, 4.2264, 4.1807, 4.1763, 4.2421, 4.1866, 4.2283, 
	4.2093, 4.2299, 4.2702, 4.2567, 4.219, 4.2562, 4.1909, 4.2676, 4.2668, 
	4.2229, 4.2735, 4.2622, 4.2236, 4.1739, 4.2973, 4.269, 4.2809, 4.2486, 
	4.2169, 4.2516, 4.204, 4.2461, 4.2177, 4.2665, 4.229, 4.1777, 4.2876, 
	4.2137, 4.2783, 4.2265, 4.2371, 4.2332, 4.1635, 4.191, 4.2361, 4.1919, 
	4.2397, 4.2258, 4.2393, 4.2402, 4.2078, 4.2065, 4.265, 4.2483, 4.1756, 
	4.2778, 4.2541, 4.2936, 4.2484, 4.2258, 4.2466, 4.2413, 4.265, 4.2619, 
	4.2155, 4.2463, 4.1995, 4.2344, 4.2354, 4.2436, 4.3086, 4.2397, 4.2624, 
	4.22, 4.1895, 4.2287, 4.2335, 4.1811, 4.2393, 4.285, 4.2179, 4.2251, 
	4.2807, 4.2725, 4.2673, 4.2069, 4.1773, 4.2586, 4.2208, 4.2524, 4.2438, 
	4.2679, 4.1849, 4.2919, 4.1954, 4.2429, 4.2323, 4.2425, 4.2644, 4.2173, 
	4.2272, 4.2638, 4.1979, 4.2597, 4.2538, 4.2258, 4.2189, 4.1952, 4.2425, 
	4.2753, 4.2589, 4.2114, 4.2296, 4.2468, 4.2158, 4.2502, 4.1844, 4.2238, 
	4.2622, 4.2226, 4.2097, 4.2768, 4.2389, 4.2232, 4.2607, 4.2243, 4.2055, 
	4.1758, 4.2855, 4.2302, 4.1991, 4.2453, 4.2533, 4.1564, 4.2343, 4.2668, 
	4.2958, 4.2071, 4.2402, 4.254, 4.2245, 4.2881, 4.2919, 4.2598, 4.3051, 
	4.2399, 4.2338, 4.257, 4.1849, 4.229, 4.2293, 4.1948, 4.2045, 4.2685, 
	4.2134, 4.2646, 4.2156, 4.2064, 4.2611, 4.233, 4.2776, 4.2225, 4.2276, 
	4.2352, 4.2235, 4.2487, 4.2305, 4.2073, 4.2368, 4.2659, 4.293, 4.2896, 
	4.1786, 4.2333, 4.2541, 4.27, 4.2197, 4.2496, 4.2635, 4.2511, 4.1762, 
	4.1891, 4.2956, 4.2887, 4.2697, 4.2088, 4.2565, 4.267, 4.2113, 4.2473, 
	4.248, 4.2097, 4.2723, 4.2325, 4.2919, 4.1906, 4.2106, 4.3116, 4.2468, 
	4.2392, 4.2365, 4.2444, 4.2024, 4.1915, 4.2348, 4.2903, 4.209, 4.2574, 
	4.2824, 4.253, 4.2262, 4.2587, 4.2534, 4.24, 4.2662, 4.1778, 4.2269, 
	4.273, 4.2629, 4.2717, 4.2312, 4.1967, 4.2193, 4.2026, 4.241, 4.2538, 
	4.2182, 4.1946, 4.199, 4.2441, 4.2459, 4.2227, 4.1953, 4.239, 4.2226, 
	4.2579, 4.1938, 4.2496, 4.2265, 4.2437, 4.2546, 4.2626, 4.2484, 4.2377, 
	4.2201, 4.2274, 4.243, 4.2214, 4.2598, 4.2301, 4.257, 4.2101, 4.1979, 
	4.2261, 4.2812, 4.2338, 4.2772, 4.2249, 4.2185, 4.2184, 4.2312, 4.2376, 
	4.2199, 4.1781, 4.2398, 4.2495, 4.2088, 4.3016, 4.2486, 4.2295, 4.2517, 
	4.2308, 4.2338, 4.2513, 4.2018, 4.2521, 4.2326, 4.1845, 4.2498, 4.2253, 
	4.2597, 4.2348, 4.2198, 4.2328, 4.2367, 4.2083, 4.2599, 4.2497, 4.2219, 
	4.2387, 4.234, 4.2423, 4.2472, 4.2821, 4.2495, 4.2341, 4.2758, 4.2673, 
	4.2422, 4.2511, 4.2008, 4.2258, 4.2301, 4.2572, 4.2607, 4.2136, 4.279, 
	4.1744, 4.2535, 4.2443, 4.188, 4.2096, 4.2339, 4.2197, 4.2108, 4.1903, 
	4.2693, 4.2256, 4.2411, 4.2756, 4.2352, 4.2328, 4.2232, 4.2156, 4.2457, 
	4.2392, 4.2039, 4.2203, 4.2101, 4.2486, 4.2467, 4.2437, 4.2439, 4.2201, 
	4.2448, 4.2527, 4.1776, 4.2391, 4.2615, 4.2647, 4.2432, 4.2279, 4.2362, 
	4.2273, 4.2437, 4.2348, 4.2469, 4.2403, 4.2581, 4.2558, 4.2498, 4.2542, 
	4.2379, 4.211, 4.1754, 4.225, 4.1995, 4.268, 4.2166, 4.2527, 4.2591, 
	4.2233, 4.2343, 4.2418, 4.2314, 4.212, 4.1927, 4.2428, 4.2407, 4.2168, 
	4.2436, 4.2109, 4.2363, 4.2206, 4.1925, 4.2327, 4.2661, 4.2416, 4.2696, 
	4.2314, 4.2081, 4.2492, 4.236, 4.2398, 4.2118, 4.2408, 4.2308, 4.2283, 
	4.2269, 4.2229, 4.2189, 4.2399, 4.2186, 4.2232, 4.2289, 4.2229, 4.2274, 
	4.2367, 4.2748, 4.2619, 4.288, 4.273, 4.2582, 4.2146, 4.2171, 4.2543, 
	4.2406, 4.2238, 4.2506, 4.2371, 4.2545, 4.2163, 4.2279, 4.2789, 4.2012, 
	4.24, 4.228, 4.2668, 4.2802, 4.2211, 4.2491, 4.2762, 4.2637, 4.2296, 
	4.2226, 4.2301, 4.1981, 4.2415, 4.2188, 4.2741, 4.243, 4.2423, 4.2321, 
	4.2297, 4.2832, 4.2238, 4.2466, 4.2392, 4.2585, 4.242, 4.2505, 4.214, 
	4.243, 4.2751, 4.244, 4.2125, 4.2188, 4.2362, 4.2181, 4.2452, 4.2363, 
	4.2313, 4.212, 4.2561, 4.2442, 4.2554, 4.2393, 4.2241, 4.2185, 4.2251, 
	4.2168, 4.2115, 4.2248, 4.2184, 4.2503, 4.2603, 4.2487, 4.2163, 4.2337, 
	4.241, 4.2749, 4.2365, 4.2199, 4.2197, 4.2226, 4.2349, 4.2709, 4.236, 
	4.2187, 4.2117, 4.2396, 4.2297, 4.204, 4.2422, 4.2405, 4.2292, 4.2585, 
	4.2281, 4.2412, 4.2331, 4.2464, 4.2568, 4.2425, 4.2173, 4.2484, 4.2267, 
	4.2539, 4.2511, 4.2388, 4.2359, 4.2109, 4.2016, 4.2346, 4.2349, 4.2405, 
	4.2331, 4.2291, 4.2176, 4.2506, 4.2148, 4.2063, 4.2046, 4.2326, 4.2407, 
	4.2406, 4.2668, 4.2687, 4.2325, 4.2365, 4.2274, 4.2122, 4.2619, 4.2463, 
	4.2217, 4.2043, 4.2137, 4.2355, 4.2772, 4.2423, 4.2495, 4.2386, 4.2923, 
	4.2193, 4.2483, 4.2197, 4.2398, 4.2346, 4.2599, 4.2308, 4.2531, 4.271, 
	4.2751, 4.2394, 4.2018, 4.2556, 4.2203, 4.2114, 4.2341, 4.2398, 4.2392, 
	4.2282, 4.2246, 4.2758, 4.2921, 4.2358, 4.1883, 4.1971, 4.2151, 4.2382, 
	4.2161, 4.2605, 4.2115, 4.2338, 4.2692, 4.2953, 4.234, 4.2463, 4.2187, 
	4.2397, 4.2629, 4.2442, 4.2366, 4.2314, 4.2314, 4.2499, 4.2369, 4.2498, 
	4.2536, 4.2369, 4.2022, 4.2582, 4.238, 4.2317, 4.2501, 4.2222, 4.2541, 
	4.2623, 4.2395, 4.2131, 4.2475, 4.2064, 4.1957, 4.2382, 4.2312, 4.23, 
	4.2381, 4.2411, 4.2657, 4.246, 4.212, 4.2403, 4.2196, 4.2477, 4.2146, 
	4.1799, 4.2388, 4.2466, 4.2346, 4.2284, 4.249, 4.2468, 4.2539, 4.2468, 
	4.2728, 4.2488, 4.1859, 4.2634, 4.1787, 4.215, 4.239, 4.2353, 4.2918, 
	4.2622, 4.2157, 4.2486, 4.2298, 4.232, 4.2121, 4.2424, 4.2384, 4.2422, 
	4.2429, 4.2433, 4.2279, 4.261, 4.2451, 4.2351, 4.237, 4.2527, 4.2458, 
	4.2352, 4.2324, 4.2524, 4.2227, 4.224, 4.2311, 4.2423, 4.2319, 4.2049, 
	4.2232, 4.2403, 4.2419, 4.2352, 4.2488, 4.2302, 4.2305, 4.2412, 4.2349, 
	4.2266, 4.2359, 4.2371, 4.2164, 4.2368, 4.2275, 4.2467, 4.2313, 4.2331, 
	4.2435, 4.2251, 4.2133, 4.232, 4.2558, 4.2364, 4.2391, 4.2487, 4.2313, 
	4.2454, 4.2233, 4.2346, 4.2288, 4.2443, 4.2196, 4.2438, 4.2369, 4.2322, 
	4.2507, 4.2246, 4.2277, 4.2411, 4.2409, 4.2472, 4.2326, 4.2326, 4.2321, 
	4.22, 4.2305, 4.2517, 4.2309, 4.2551, 4.2295, 4.238, 4.2408, 4.2313, 
	4.2465, 4.2273, 4.2291, 4.2363, 4.2472, 4.2351, 4.2098, 4.2329, 4.2195, 
	4.238, 4.2104, 4.2295, 4.2347, 4.2274, 4.2284, 4.2489, 4.2424, 4.2392, 
	4.243, 4.217, 4.2161, 4.237, 4.2327, 4.2418, 4.2402, 4.2355, 4.2513, 
	4.2342, 4.2411, 4.2359, 4.2417, 4.2306, 4.2323, 4.2268, 4.2191, 4.2401, 
	4.2298, 4.233, 4.2554, 4.2324, 4.2281, 4.2467, 4.2447, 4.2375, 4.2278, 
	4.2354, 4.2376, 4.2298, 4.2373, 4.2323, 4.2463, 4.2333, 4.2447, 4.2259, 
	4.2325, 4.2287, 4.2393, 4.2323, 4.2157, 4.2261, 4.2289, 4.2498, 4.2431, 
	4.2266, 4.2338, 4.2354, 4.2321, 4.2441, 4.2303, 4.2286, 4.2599, 4.2355, 
	4.2386, 4.2389, 4.2297, 4.2376, 4.2226, 4.2371, 4.2303, 4.2285, 4.2222, 
	4.2277, 4.233, 4.2205, 4.2326, 4.2341, 4.24, 4.2345, 4.2324, 4.2424, 
	4.2288, 4.2587, 4.2498, 4.2361, 4.2281, 4.2433, 4.2224, 4.2301, 4.2208, 
	4.2211, 4.2429, 4.2436, 4.2301, 4.2382, 4.2436, 4.2521, 4.2413, 4.2465, 
	4.2324, 4.2329, 4.2422, 4.2293, 4.2137, 4.2219, 4.2297, 4.2229, 4.2227, 
	4.2361, 4.2353, 4.245, 4.2361, 4.2281, 4.239, 4.2415, 4.2476, 4.2458, 
	4.2326, 4.2496, 4.2462, 4.2472, 4.2268, 4.2535, 4.2327, 4.2343, 4.2503, 
	4.2441, 4.2284, 4.2492, 4.2513, 4.2294, 4.2339, 4.2349, 4.2495, 4.2356, 
	4.2333, 4.2301, 4.2433, 4.2338, 4.2461, 4.2363, 4.2383, 4.2358, 4.2429, 
	4.2401, 4.2534, 4.2477, 4.2229, 4.2471, 4.2462, 4.2366, 4.2438, 4.2167, 
	4.2355, 4.2477, 4.2324, 4.2313, 4.245, 4.2376, 4.2244, 4.2271, 4.2199, 
	4.2298, 4.2433, 4.2301, 4.2534, 4.2342, 4.2338, 4.2307, 4.229, 4.2261, 
	4.2286, 4.2137, 4.2507, 4.2341, 4.2338, 4.2423, 4.2509, 4.2217, 4.2354, 
	4.2394, 4.2357, 4.2248, 4.2392, 4.2499, 4.2433, 4.2345, 4.2433, 4.2588, 
	4.2216, 4.2419, 4.2292, 4.2365, 4.2345, 4.2308, 4.2425, 4.2518, 4.2251, 
	4.2201, 4.2233, 4.2208, 4.23, 4.245, 4.2384, 4.246, 4.2395, 4.2398, 
	4.2371, 4.2487, 4.2286, 4.2466, 4.2431, 4.22, 4.2262, 4.2393, 4.2425, 
	4.234, 4.241, 4.2398, 4.2276, 4.2303, 4.232, 4.2347, 4.2346, 4.2204, 
	4.233, 4.2291, 4.228, 4.2384, 4.2218, 4.2259, 4.2253, 4.2496, 4.2411, 
	4.2355, 4.2443, 4.23, 4.2335, 4.2216, 4.2353, 4.2338, 4.2366, 4.2167, 
	4.2406, 4.2266, 4.2201, 4.2391, 4.2173, 4.2638, 4.2435, 4.2262, 4.2454, 
	4.2536, 4.2353, 4.2299, 4.2278, 4.2334, 4.2284, 4.2365, 4.231, 4.2333, 
	4.2417, 4.2254, 4.2302, 4.2132, 4.2388, 4.2305, 4.2359, 4.2314, 4.2187, 
	4.2455, 4.2397, 4.2365, 4.237, 4.234, 4.2311, 4.2402, 4.2361, 4.2187, 
	4.2312, 4.2649, 4.2313, 4.2528, 4.2328, 4.2379, 4.2422, 4.2472, 4.2335, 
	4.2582, 4.2354, 4.2328, 4.2314, 4.2361, 4.2375, 4.2362, 4.2256, 4.2155, 
	4.2245, 4.2247, 4.2342, 4.2474, 4.2593, 4.2462, 4.2388, 4.2225, 4.244, 
	4.2253, 4.2274, 4.2383, 4.2459, 4.2438, 4.2284, 4.2231), .Dim = c(400, 
	8), .Dimnames = list(character(0), c("size1L", "size2L", "size4L", 
	"size10L", "size25L", "size50L", "size100L", "size625L")))
"census4"<-
structure(.Data = list(size1M = c(34.653, 6.677, 13.872, 14.125, 42.508, 
	16.866, 16.965, 28.651, 19.907, 17.352, 8.344, 37.077, 17.439, 
	13.357, 7.243, 13.505, 19.547, 31.849, 18.421, 16.079, 19.57, 
	16.327000000000002, 31.11, 17.738, 15.884, 7.563, 9.696, 40.022, 
	28.568, 14.054, 10.579, 8.355, 10.422, 15.95, 26.359, 25.441, 
	10.853, 12.263, 15.691, 17.565999999999998, 23.983, 8.4, 
	17.457999999999998, 11.688, 7.851, 16.672999999999998, 9.47, 
	9.8510000000000016, 11.517, 23.959, 17.439, 15.643, 24.094, 22.474,
	18.949, 42.026, 39.651, 40.634, 11.568, 16.815000000000002, 20.537,
	16.924, 28.903, 34.418, 25.937, 18.244, 5.9, 22.651, 13.872, 
	11.634, 0.518, 28.481, 9.0559999999999984, 58.364, 12.86, 13.879, 
	23.493, 29.486, 16.739, 6.585, 26.187, 34.229, 44.963, 22.891, 
	12.855, 13.901, 31.314, 21.637, 13.684, 16.315000000000002, 6.934, 
	13.589, 28.748, 18.909, 14.304, 9.494, 6.243, 17.193000000000002, 
	28.622, 12.171, 18.536, 16.866, 29.135, 20.606, 10.824, 21.457, 
	27.281, 22.625, 89.585, 10.443, 20.554, 8.843, 12.389, 22.536, 
	13.518, 25.123, 14.548, 29.363, 8.473, 23.264, 22.718, 25.713, 
	21.102, 11.606, 26.229, 34.027, 8.766, 12.414, 14.217, 34.958, 
	15.421, 17.928999999999998, 31.981, 14.401, 18.371, 19.954, 15.126,
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"census5"<-
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"census6"<-
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"chal"<-
structure(.Data = list(temp = c(53, 57, 58, 63, 66, 67, 67, 67, 68, 69, 70,
	70, 70, 70, 72, 73, 75, 75, 76, 76, 78, 79, 81), numdam = c(2, 1, 
	1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 0, 0, 0, 2, 0, 0, 0, 0, 0)), 
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20", "21", "22", "23"))
"demand"<-
structure(.Data = list(yr = c(60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 
	71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86), g
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	148.80000000000002, 155.9, 164.9, 171, 183.4, 195.8, 207.4, 218.3, 
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	225.6, 228.8, 239.6, 244.7, 245.8, 269.39999999999996), pg = c(
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	2.656, 3.691, 4.109, 3.894, 3.764, 3.707, 3.738, 2.921), i = c(
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	9725, 9930, 10421, 10563, 10780), pnc = c(1.045, 1.045, 1.041, 
	1.035, 1.032, 1.0089999999999998, 0.991, 1, 1.028, 1.044, 1.076, 
	1.1200000000000002, 1.11, 1.111, 1.175, 1.276, 1.357, 1.429, 1.538,
	1.66, 1.793, 1.902, 1.976, 2.026, 2.085, 2.152, 2.2400000000000004
	), puc = c(0.836, 0.869, 0.948, 0.96, 1.0009999999999998, 0.994, 
	0.97, 1, 1.028, 1.031, 1.043, 1.102, 1.105, 1.176, 1.226, 1.464, 
	1.679, 1.828, 1.865, 2.0099999999999996, 2.081, 2.569, 2.964, 
	3.297, 3.757, 3.797, 3.632), ppt = c(0.81, 0.846, 0.874, 0.885, 
	0.901, 0.919, 0.952, 1, 1.046, 1.127, 1.285, 1.377, 1.434, 1.448, 
	1.48, 1.586, 1.742, 1.824, 1.878, 2.003, 2.516, 3.12, 3.46, 3.626, 
	3.852, 4.0279999999999992, 4.264), pd = c(0.444, 0.448, 0.457, 
	0.463, 0.47, 0.471, 0.475, 0.483, 0.501, 0.514, 0.527, 
	0.54700000000000008, 0.55500000000000008, 0.56599999999999992, 
	0.604, 0.659, 0.69499999999999992, 0.727, 0.769, 0.821, 0.892, 
	0.957, 1, 1.041, 1.038, 1.045, 1.053), pn = c(0.331, 0.335, 
	0.33800000000000004, 0.34300000000000004, 0.34699999999999996, 
	0.353, 0.366, 0.375, 0.39, 0.409, 0.427, 0.442, 0.458, 0.497, 
	0.57199999999999992, 0.615, 0.638, 0.67100000000000008, 0.719, 0.8,
	0.894, 0.969, 1, 1.021, 1.05, 1.075, 1.069), ps = c(0.302, 0.307, 
	0.314, 0.32, 0.325, 0.332, 0.34200000000000004, 0.353, 0.368, 
	0.386, 0.407, 0.431, 0.451, 0.474, 0.513, 0.55600000000000008, 
	0.598, 0.648, 0.69799999999999992, 0.756, 0.839, 0.926, 1, 1.062, 
	1.117, 1.173, 1.224), yrsq = c(3600, 3721, 3844, 3969, 4096, 4225, 
	4356, 4489, 4624, 4761, 4900, 5041, 5184, 5329, 5476, 5625, 5776, 
	5929, 6084, 6241, 6400, 6561, 6724, 6889, 7056, 7225, 7396)), 
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20", "21", "22", "23", "24", "25", "26", "27"))
"djsp"<-
structure(.Data = list(week = structure(.Data = c(54, 58, 62, 66, 71, 74, 
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	122, 125, 128, 131, 134, 137, 140, 143, 146, 149, 152, 155, 158, 
	161, 16, 19, 22, 25, 28, 31, 34, 37, 40, 43, 46, 49, 52, 2, 5, 8, 
	11, 55, 59, 63, 67, 70, 73, 76, 79, 82, 85, 88, 91, 94, 97, 100, 
	103, 106, 109, 112, 115, 118, 121, 124, 127, 130, 133, 136, 139, 
	142, 145, 148, 151, 154, 157, 160, 15, 18, 21, 24, 27, 30, 33, 36, 
	39, 42, 45, 48, 51, 1, 4, 7, 10, 13, 57, 61, 65, 69, 72, 75, 78, 
	81, 84, 87, 90, 93, 96, 99, 102, 105, 108, 111, 114, 117, 120, 123,
	126, 129, 132, 135, 138, 141, 144, 147, 150, 153, 156, 159, 14, 17,
	20, 23, 26, 29, 32, 35, 38, 41, 44, 47, 50, 53, 3, 6, 9, 12, 56, 
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	"12/ 3/93", "12/ 5/92", "12/ 6/91", "12/10/93", "12/12/92", 
	"12/13/91", "12/17/93", "12/19/92", "12/20/91", "12/24/93", 
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	"8/ 9/91", "8/13/93", "8/15/92", "8/16/91", "8/20/93", "8/22/92", 
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	"9/ 6/91", "9/10/93", "9/12/92", "9/13/91", "9/17/93", "9/19/92", 
	"9/20/91", "9/24/93", "9/26/92", "9/27/91"), class = "factor"), 
	dji = c(2730.69, 2830.69, 2934.65, 2889.36, 2909.9, 2955.2, 
	2948.27, 2858.91, 2913.86, 2896.7800000000004, 2920.79, 2965.59, 
	2912.38, 2938.86, 2920.17, 2886.63, 2913.91, 3027.5, 
	2976.7399999999996, 3000.45, 2965.56, 2906.75, 2932.4699999999996, 
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	3040.25, 3043.6, 3011.63, 2985.69, 3019.23, 3006.04, 
	2961.7600000000004, 2983.68, 3077.15, 3004.92, 3056.35, 3045.62, 
	2943.2, 2902.73, 2894.68, 2886.4, 2914.36, 2934.48, 3101.52, 
	3201.48, 3199.46, 3264.98, 3232.7800000000004, 3223.39, 3225.4, 
	3245.9699999999996, 3280.19, 3267.67, 3221.6, 3235.91, 3276.39, 
	3231.44, 3249.11, 3255.37, 3366.5, 3324.46, 3336.09, 3369.41, 
	3353.09, 3386.77, 3396.88, 3398.69, 3354.36, 3285.35, 3282.41, 
	3330.29, 3330.56, 3331.64, 3285.71, 3393.7800000000004, 3332.18, 
	3328.94, 3254.1, 3267.61, 3281.93, 3305.7, 3327.05, 3250.32, 
	3200.61, 3136.58, 3174.41, 3207.64, 3226.2800000000004, 3240.06, 
	3233.0300000000004, 3227.36, 3282.2, 3288.68, 3304.08, 3313.27, 
	3326.2399999999996, 3301.11, 3251.67, 3271.12, 3256.81, 
	3310.0300000000004, 3442.14, 3392.43, 3322.18, 3370.81, 3404.58, 
	3427.82, 3471.58, 3439.98, 3370.81, 3396.48, 3478.61, 3413.77, 
	3427.55, 3437.19, 3443.0100000000004, 3492.83, 3527.43, 3545.14, 
	3505.0100000000004, 3494.77, 3490.89, 3483.9699999999996, 3521.06, 
	3528.29, 3546.7399999999996, 3539.4699999999996, 3560.43, 3569.65, 
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	3584.7399999999996, 3629.73, 3649.3, 3680.59, 3643.43, 3684.51, 
	3694.01, 3683.95, 3704.07, 3740.67, 3751.57, 3757.72, 3754.09, 
	3820.77, 3867.2, 3914.48, 3945.43, 3871.42, 3894.78, 3887.46, 
	3838.78), sp = c(343.05, 359.35000000000004, 369.06, 365.65, 
	370.47, 374.95, 373.59, 367.48, 375.22, 375.36, 380.4, 384.2, 
	379.02, 380.8, 375.74, 372.39, 377.49, 389.83, 379.43, 382.29, 
	377.75, 371.16, 374.08, 380.25, 384.22, 380.93, 387.18, 387.12, 
	385.58, 394.17, 395.43, 389.1, 383.59, 387.92, 385.9, 381.25, 
	381.45, 392.5, 384.2, 391.32, 392.89, 382.62, 376.14, 375.22, 
	379.1, 384.47, 387.04, 406.46, 419.34, 415.1, 418.86, 415.48, 
	408.78, 411.09, 412.48, 411.43, 412.7, 404.44, 405.84, 411.25, 
	403.5, 401.55, 404.29, 416.04, 409.02, 412.53, 416.05, 410.09, 
	414.02, 415.35, 413.48, 409.76, 403.67, 403.45, 411.77, 414.62, 
	415.62, 411.6, 424.22, 418.88, 419.91, 414.85, 414.84, 417.08, 
	419.58, 422.93, 414.35, 410.47, 402.66, 411.73, 414.1, 418.68, 
	417.58, 422.43, 426.65, 430.16, 432.06, 433.73, 441.28, 439.77, 
	435.71, 429.05, 437.15, 436.11, 438.78, 448.93, 444.58, 434.22, 
	443.38, 446.11, 449.83, 450.18, 447.78, 441.39, 441.84, 448.94, 
	437.03, 440.19, 442.31, 439.56, 445.84, 450.19, 450.06, 447.26, 
	443.68, 447.6, 445.84, 448.11, 445.75, 447.1, 448.13, 448.68, 
	450.14, 456.16, 460.54, 461.34, 461.72, 458.83, 457.63, 461.28, 
	460.31, 469.5, 463.27, 467.83, 459.57, 465.39, 462.6, 463.06, 
	464.89, 463.93, 466.38, 467.38, 466.45, 469.9, 474.91, 474.72, 
	478.7, 469.81, 470.18, 467.69, 466.07)), class = "data.frame", 
	row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", 
	"11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", 
	"22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", 
	"33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", 
	"44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", 
	"55", "56", "57", "58", "59", "60", "61", "62", "63", "64", "65", 
	"66", "67", "68", "69", "70", "71", "72", "73", "74", "75", "76", 
	"77", "78", "79", "80", "81", "82", "83", "84", "85", "86", "87", 
	"88", "89", "90", "91", "92", "93", "94", "95", "96", "97", "98", 
	"99", "100", "101", "102", "103", "104", "105", "106", "107", 
	"108", "109", "110", "111", "112", "113", "114", "115", "116", 
	"117", "118", "119", "120", "121", "122", "123", "124", "125", 
	"126", "127", "128", "129", "130", "131", "132", "133", "134", 
	"135", "136", "137", "138", "139", "140", "141", "142", "143", 
	"144", "145", "146", "147", "148", "149", "150", "151", "152", 
	"153", "154", "155", "156", "157", "158", "159", "160", "161"))
"elusage"<-
structure(.Data = list(month = c(8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 
	9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 
	5, 6, 7, 8, 9, 10, 11, 12, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
	1, 2), year = c(1989, 1989, 1989, 1989, 1989, 1990, 1990, 1990, 
	1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1991, 1991, 
	1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1992, 
	1992, 1992, 1992, 1992, 1992, 1992, 1992, 1992, 1992, 1992, 1992, 
	1993, 1993, 1993, 1993, 1993, 1993, 1993, 1993, 1993, 1993, 1993, 
	1993, 1994, 1994), kwh = c(24.828, 24.688, 19.31, 59.706, 99.667, 
	49.333, 59.375, 55.172, 55.517, 25.938, 20.69, 24.333, 22.759, 
	24.688, 22.759, 50.588, 79, 87.188, 47.333, 38.621, 27.931, 25, 
	17.241, 17, 22.188, 18.276, 27.241, 39.706, 81.667, 79.688, 67.667,
	65.861999999999992, 54.839, 34.667, 23.448, 29.586, 32.448, 30.033,
	43.586, 48.029, 52.424, 62.333, 71.156000000000008, 44.621, 19.357,
	23.733, 10.414, 17.875, 24.207, 24.333, 40.935, 42.938, 65.25, 
	101.3, 101.66), temperature = c(73, 67, 57, 43, 26, 41, 38, 46, 54,
	60, 71, 75, 74, 66, 61, 49, 41, 35, 41, 42, 56, 69, 73, 77, 74, 66,
	56, 47, 38, 34, 37, 39, 51, 60, 70, 73, 71, 66, 54, 45, 36, 34, 32,
	39, 55, 64, 72, 79, 75, 65, 54, 48, 35, 24, 32)), class = 
	"data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8",
	"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
	"20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", 
	"31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", 
	"42", "43", "44", "45", "46", "47", "48", "49", "50", "51", "52", 
	"53", "54", "55"))
"empl"<-
structure(.Data = list(year = c(1971, 1972, 1973, 1974, 1975, 1976, 1977, 
	1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 
	1989, 1990), employ = c(87.9, 88.5, 88.8, 90.2, 78.1, 79.6, 81.5, 
	82.4, 80.5, 77.7, 76.7, 73.2, 69.3, 72.2, 76, 73.3, 75, 75.5, 77.6,
	75.9)), class = "data.frame", row.names = c("1", "2", "3", "4", 
	"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", 
	"17", "18", "19", "20"))
"ers"<-
structure(.Data = list(date = structure(.Data = c(1, 3, 5, 7, 9, 11, 13, 
	15, 17, 19, 21, 23, 25, 27, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22,
	24, 26, 28), .Label = c("16/93", "16/94", "17/93", "17/94", 
	"18/93", "18/94", "19/93", "19/94", "20/93", "20/94", "21/93", 
	"21/94", "22/93", "22/94", "23/93", "23/94", "24/93", "24/94", 
	"25/93", "25/94", "26/93", "26/94", "27/93", "27/94", "28/93", 
	"28/94", "29/93", "29/94"), class = "factor"), calls = c(2298, 
	1709, 2395, 2486, 1849, 1842, 2100, 1752, 1776, 1812, 1842, 1674, 
	1692, 1879, 6375, 8827, 7218, 8810, 7841, 7745, 6454, 4619, 6476, 
	4692, 3638, 8947, 6564, 5613), fhigh = c(38, 41, 33, 29, 40, 44, 
	46, 47, 53, 38, 35, 39, 34, 46, 17, 35, 30, 10, 15, 24, 33, 32, 48,
	38, 26, 29, 48, 31), flow = c(31, 27, 26, 19, 19, 30, 40, 35, 34, 
	32, 21, 27, 28, 28, 9, 15, 32, 4, 6, 12, 19, 18, 30, 32, 23, 14, 
	34, 40), high = c(39, 41, 38, 36, 43, 43, 53, 46, 55, 43, 35, 44, 
	40, 41, 15, 47, 35, 10, 15, 21, 32, 32, 49, 42, 32, 31, 55, 36), 
	low = c(31, 30, 24, 21, 27, 29, 41, 40, 38, 31, 25, 31, 27, 23, 3, 
	12, 4, -2, 0, 6, 15, 18, 31, 32, 5, 0, 31, 36), rain = c(0, 0, 0, 
	0, 0, 0, 1, 0, 1, 0, 0, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 0, 0, 0, 1, 
	0, 1, 1), snow = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 1, 
	0, 0, 1, 0, 0, 0, 0, 0, 1, 0, 1, 1), weekday = c(0, 0, 0, 1, 1, 1, 
	1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0), 
	year = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 
	1, 1, 1, 1, 1, 1, 1, 1, 1), sunday = c(0, 1, 0, 0, 0, 0, 0, 0, 1, 
	0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0), subzero
	 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 1, 1, 0,
	0, 0, 0, 0, 1, 0, 0)), class = "data.frame", row.names = c("1", 
	"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
	"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
	"25", "26", "27", "28"))
"foot"<-
structure(.Data = list(favname = structure(.Data = c(2, 3, 5, 18, 16, 7, 
	14, 20, 22, 13, 26, 21, 9, 28, 1, 19, 10, 14, 12, 17, 3, 18, 5, 28,
	25, 4, 26, 2, 11, 10, 3, 14, 24, 7, 16, 18, 15, 19, 21, 17, 28, 4, 
	9, 4, 5, 20, 26, 10, 2, 19, 8, 22, 13, 16, 28, 3, 14, 2, 3, 4, 5, 
	9, 16, 10, 25, 26, 21, 28, 7, 20, 27, 16, 3, 7, 13, 4, 1, 18, 21, 
	5, 26, 24, 19, 14, 22, 12, 25, 15, 4, 21, 16, 26, 14, 19, 2, 10, 
	28, 5, 18, 9, 5, 23, 3, 2, 11, 7, 22, 25, 26, 4, 28, 19, 2, 3, 4, 
	5, 10, 15, 16, 19, 17, 21, 7, 12, 28, 26, 26, 3, 5, 22, 12, 9, 2, 
	15, 16, 18, 14, 21, 13, 10, 2, 4, 26, 5, 10, 15, 16, 18, 14, 23, 
	19, 3, 11, 28, 5, 21, 20, 3, 2, 10, 16, 13, 15, 11, 7, 22, 14, 26, 
	5, 13, 9, 10, 17, 14, 12, 18, 24, 19, 26, 28, 16, 2, 16, 5, 21, 3, 
	9, 2, 7, 13, 20, 28, 4, 10, 15, 14, 19, 7, 26, 3, 4, 11, 16, 23, 
	14, 12, 8, 28, 25, 21, 2, 25, 10, 26, 7, 8, 9, 18, 15, 19, 14, 21, 
	23, 16, 15, 8, 3, 14, 28, 16, 2, 24, 7, 1, 4, 5, 19, 26, 11, 2, 4, 
	5, 8, 9, 14, 16, 19, 21, 23, 26, 13, 7, 4, 3, 5, 7, 9, 10, 13, 14, 
	18, 19, 26, 27, 28, 2, 20, 2, 8, 12, 13, 15, 16, 19, 21, 24, 28, 4,
	25, 1, 27, 3, 12, 14, 15, 16, 24, 26, 2, 7, 7, 10, 12, 13, 18, 20, 
	22, 26, 27, 28, 3, 21, 15, 2, 7, 13, 14, 19, 26, 25, 27, 28, 10, 5,
	2, 18, 15, 9, 10, 21, 3, 26, 24, 19, 4, 14, 21, 2, 3, 4, 12, 14, 
	15, 20, 23, 26, 25, 28, 7, 19, 17, 15, 8, 12, 18, 3, 2, 19, 24, 13,
	26, 21, 2, 3, 9, 10, 12, 14, 19, 20, 21, 26, 25, 28, 4, 15, 7, 28, 
	22, 3, 4, 9, 13, 15, 18, 19, 23, 26, 24, 10, 12, 1, 2, 3, 13, 14, 
	16, 18, 23, 22, 24, 25, 28, 26, 23, 1, 2, 9, 10, 12, 14, 15, 19, 
	26, 28, 13, 19, 28, 1, 3, 6, 7, 12, 13, 15, 16, 18, 20, 21, 26, 8, 
	13, 28, 20, 2, 3, 10, 12, 14, 21, 23, 19, 26, 25, 12, 21, 15, 28, 
	4, 1, 19, 26, 25, 7, 27, 13, 23, 18, 11, 20, 6, 18, 12, 21, 3, 23, 
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	8, 12, 13, 15, 18, 19, 21, 26, 28, 22, 3, 22, 2, 8, 12, 14, 15, 19,
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	26, 5, 3, 20, 28, 6, 16, 18, 15, 7, 19, 15, 2, 4, 5, 7, 8, 10, 12, 
	18, 19, 20, 25, 28, 16, 20, 1, 3, 8, 10, 12, 13, 16, 18, 19, 21, 
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	6, 7, 5, 2, 15, 28, 25, 26, 19, 1, 13, 10, 17, 5, 3, 6, 19, 10, 12,
	28, 1, 13, 8, 26, 16, 15, 3, 26, 20, 23, 21, 1, 8, 10, 7, 16, 28, 
	15, 2, 18, 10, 16, 13, 27, 28, 6, 18, 23, 15, 2, 7, 17, 25, 26), 
	.Label = c("ATL", "BUF", "CHI", "CIN", "CLE", "DAL", "DEN", "DET", 
	"GB", "HOU", "IND", "KC", "LAA", "LAN", "MIA", "MIN", "NE", "NO", 
	"NYG", "NYJ", "PHA", "PHX", "PIT", "SD", "SEA", "SF", "TB", "WAS"),
	class = "factor"), undname = structure(.Data = c(15, 4, 23, 6, 10, 
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	13, 19, 9, 12, 11, 21, 1, 22, 5, 20, 8, 24, 4, 14, 3), .Label = c(
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	"HOU", "IND", "KC", "LAA", "LAN", "MIA", "MIN", "NE", "NO", "NYG", 
	"NYJ", "PHA", "PHX", "PIT", "SD", "SEA", "SF", "TB", "WAS"), class
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	-1, -1, -1, -1, -1, -1, 1, -1, -1, 1, 1, 1, -1, -1, 1, 1, 1, -1, 1,
	1, -1, -1, 1, 1, 1, -1, 1, 1, -1, 1, 1, -1, 1, -1, 1, 1, -1, -1, 1,
	-1, 1, 1, -1, -1, 1, 1, 1, -1, 0, 1, 1, 1, 1, -1, -1, 1, -1, 1, -1,
	1, -1, -1, 1, -1, 1, 1, 1, -1, 1, 1, -1, 1, -1, 1, 1, -1, 1, -1, 0,
	1, -1, 1, 1, -1, -1, -1, 1, -1, -1, 1, -1, 1, -1, -1, 1, -1, -1, 0,
	1, -1, 1, -1, 1, 1, 1, -1, -1, 1, 1, 1, 1, 1, 1, -1, 1, -1, 1, 1, 
	-1
	, 1, 1, -1, -1, 1, -1, 1, -1, -1, 1, 1, -1, 1, 1, -1, -1, -1, 1, 1,
	1, 1, -1, 1, 1, 1, -1, 1, -1, 1, 1, -1, -1, 0, 1, -1, -1, 1, -1, 1,
	-1, 0, 1, 1, -1, -1, -1, -1, -1, 1, 1, -1, 1, 1, 1, 1, 1, -1, 1, 
	-1, 1, 0, -1, -1, -1, -1, 1, 1, 1, -1, -1, -1, 1, 1, -1, 0, 0, -1, 
	1, -1, -1, -1, -1, -1, -1, 1, 0, -1, 1, 1, -1, -1, -1, 1, -1, -1, 
	-1
	, 1, -1, 1, 1, 1, -1, -1, 1, 1, 1, -1, -1, -1, -1, 1, -1, 1, -1, 1,
	1, 1, 1, 1, 1, -1, -1, 1, 1, -1, 1, -1, 1, 1, 0, 1, 1, 1, 1, -1, 1,
	-1, -1, 1, -1, -1, 1, -1, -1, 0, -1, -1, 1, -1, 1, -1, 1, -1, -1, 
	1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, 1, -1, -1, 1, 1, 1, -1, 1, 
	-1, 1, 1, -1, -1, -1, -1, -1, 1, 1, 0, -1, -1, 1, -1, 1, 1, 1, 1, 
	-1
	, -1, 1, 1, -1, 1, -1, -1, 1, 1, -1, -1, -1, -1, -1, -1, 1, -1, -1,
	1, 0, 1, -1, 1, 1, 1, 1, 1, 1, 1, 1, -1, 1, -1, -1, -1, -1, -1, -1,
	1, 1, -1, 1, -1, -1, 1, -1, 1, -1, -1, 1, 1, 1, -1, 1, -1, 1, 1, 0,
	-1, -1, 1, -1, 1, 1, -1, -1, -1, 1, -1, 1, 1, 1, -1, -1, 1, -1, 1, 
	1), day = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 1, 2, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	1, 2, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 4, 4, 4, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 3, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 
	0, 2, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 2, 4, 4, 0, 1, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 2, 4, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 3, 4, 4, 
	0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 1, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 0, 0, 0, 0, 0, 0, 
	0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 1, 2, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 
	0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	0, 0, 0, 1, 2, 3, 3, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 0, 0, 0, 0, 
	0, 0, 0, 0, 0, 0, 0, 0, 1, 2, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
	1, 2, 4, 4, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 2), homeaway = c(0, 1,
	0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 
	1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 
	1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 0, 0, 0, 0, 1, 1, 0, 1, 0, 1, 1, 
	1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 
	0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 1, 
	0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 0, 1, 1, 0, 1, 0, 
	0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 1, 1, 1, 1, 1, 0, 0, 
	1, 0, 1, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 
	0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 
	1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 1, 0, 1, 
	0, 1, 0, 1, 1, 0, 1, 0, 1, 0, 0, 1, 1, 1, 1, 0, 1, 0, 0, 0, 1, 1, 
	0, 1, 0, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 
	0, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 0, 0, 1, 0, 1, 0, 1, 1, 1, 0, 0, 
	1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 
	1, 1, 1, 1, 0, 1, 0, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 0, 1, 1, 1, 
	1, 1, 1, 0, 1, 0, 0, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 0, 
	0, 0, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 1, 0, 
	0, 1, 1, 1, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 
	1, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 0, 
	0, 0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 1, 0, 0, 1, 1, 1, 1, 0, 0, 
	1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 
	1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 1, 
	1, 0, 1, 1, 0, 0, 1, 0, 1, 0, 1, 1, 1, 1, 1, 0, 1, 1, 1, 1, 1, 0, 
	1, 0, 0, 0, 0, 1, 1, 1, 0, 1, 0, 1, 0, 0, 1, 0, 1, 1, 0, 0, 1, 1, 
	0, 1, 1, 1, 0, 1, 1, 1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 0, 1, 1, 1, 0, 
	1, 1, 1, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 1, 1, 1, 1, 1, 0, 0, 1, 
	0, 1, 0, 1, 1, 1, 0, 1, 0, 1, 0, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 
	0, 0, 1, 1, 1, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 1, 1, 1, 0, 1, 
	1, 1, 0, 1, 1, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 
	1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 0, 0, 1, 1, 1, 0, 0, 1, 0, 1, 1, 1, 
	0, 1, 0, 1, 1, 1, 0, 0, 1, 1), week = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 
	1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 
	3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 
	4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 6, 
	6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 
	7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 
	9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 
	10, 10, 10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11,
	12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13,
	13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14,
	14, 14, 14, 14, 14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15, 15,
	15, 15, 15, 15, 15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16,
	16, 16, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2,
	2, 2, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 
	4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 
	5, 5, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 
	7, 7, 7, 7, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 
	9, 9, 9, 9, 9, 9, 9, 9, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,
	10, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 11, 12, 12,
	12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 12, 13, 13, 13, 13, 13,
	13, 13, 13, 13, 13, 13, 13, 13, 13, 14, 14, 14, 14, 14, 14, 14, 14,
	14, 14, 14, 14, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15,
	15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 17,
	17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 1, 1, 1, 1, 1, 1, 
	1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 
	3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 3, 4, 4, 4, 4, 4, 4, 4, 4, 
	4, 4, 4, 4, 4, 4, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 5, 6, 6, 6, 6, 
	6, 6, 6, 6, 6, 6, 6, 6, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 7, 8, 8, 8, 
	8, 8, 8, 8, 8, 8, 8, 8, 8, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 9, 10, 
	10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 11, 11, 11, 11, 11, 11,
	11, 11, 11, 11, 11, 11, 11, 11, 12, 12, 12, 12, 12, 12, 12, 12, 12,
	12, 12, 12, 12, 12, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13, 13,
	13, 13, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 14, 15, 15,
	15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 16, 16, 16, 16, 16,
	16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 17, 17, 17, 17,
	17, 17, 17, 17, 17, 17), year = c(89, 89, 89, 89, 89, 89, 89, 89, 
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89,
	89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 89, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
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	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
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	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
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	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90,
	90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 90, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91, 91,
	91)), class = "data.frame", row.names = c("1", "2", "3", "4", "5", 
	"6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17",
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	"29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", 
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	"492", "493", "494", "495", "496", "497", "498", "499", "500", 
	"501", "502", "503", "504", "505", "506", "507", "508", "509", 
	"510", "511", "512", "513", "514", "515", "516", "517", "518", 
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	"528", "529", "530", "531", "532", "533", "534", "535", "536", 
	"537", "538", "539", "540", "541", "542", "543", "544", "545", 
	"546", "547", "548", "549", "550", "551", "552", "553", "554", 
	"555", "556", "557", "558", "559", "560", "561", "562", "563", 
	"564", "565", "566", "567", "568", "569", "570", "571", "572", 
	"573", "574", "575", "576", "577", "578", "579", "580", "581", 
	"582", "583", "584", "585", "586", "587", "588", "589", "590", 
	"591", "592", "593", "594", "595", "596", "597", "598", "599", 
	"600", "601", "602", "603", "604", "605", "606", "607", "608", 
	"609", "610", "611", "612", "613", "614", "615", "616", "617", 
	"618", "619", "620", "621", "622", "623", "624", "625", "626", 
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	"636", "637", "638", "639", "640", "641", "642", "643", "644", 
	"645", "646", "647", "648", "649", "650", "651", "652", "653", 
	"654", "655", "656", "657", "658", "659", "660", "661", "662", 
	"663", "664", "665", "666", "667", "668", "669", "670", "671", 
	"672"))
"free"<-
structure(.Data = list(player = structure(.Data = c(126, 96, 115, 120, 16, 
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	93, 47, 56, 17, 18, 19, 7, 48, 28, 67, 20, 57, 95, 9, 1, 122, 10, 
	49, 12, 30, 69, 91, 113, 2, 66, 123, 106, 31, 41, 42, 152, 116, 
	118, 145, 92, 150, 157, 3, 58, 32, 128, 74, 107, 119, 129, 130, 
	131, 97, 156, 133, 75, 108, 114, 158, 51, 117, 77, 78, 159, 109, 
	135, 79, 4, 35, 98, 55, 136, 44, 80, 81, 99, 160, 61, 5, 62, 121, 
	83, 84, 101, 149, 52, 22, 23, 139, 64, 36, 37, 38, 110, 111, 53, 
	65, 25, 155, 88, 89, 90, 104, 94, 151, 68, 45, 105, 70, 71, 21, 
	112, 125, 127, 142, 102, 132, 103, 134, 76, 154, 43, 100, 46, 86, 
	137, 138, 15, 87, 24, 39), .Label = c("A. Bumbry", "A. Dawson", 
	"A. Howe", "A. Otis", "A. Rodriguez", "A. Thornton", "B. Ayala", 
	"B. Bochte", "B. Brenly", "B. Butler", "B. Campaneris", "B. Carbo",
	"B. Grich", "B. Russell", "B. Stein", "B. Watson", 
	"Bill Almon (79-80)", "Bill Almon (82-83)", "Bill Almon (85-86)", 
	"Bob Boone", "C. Fisk", "C. Speier (84-85)", "C. Speier (86-87)", 
	"C. Washington (80-81)", "C. Washington (88-89)", "Cliff Johnson", 
	"D. Baylor (76-77)", "D. Baylor (82-83)", "D. Cash", "D. Chalk", 
	"D. Dyer", "D. Iorg", "D. Kingman", "D. Kingman (77-78)", 
	"D. Parker", "D. Thomas (78-79)", "D. Thomas (83-84)", "D. Thon", 
	"D. Winfield", "Darrell Evans (76-77)", "Darrell Evans (83-84)", 
	"Darrell Evans (88-89)", "Darrell Porter(80-81)", 
	"Darrell Porter(85-86)", "Dave Collins", "Dave Roberts", 
	"Dick Allen", "Dusty Baker", "E. Cabell", "E. Maddox", "E. Milner",
	"E. Soderholm", "E. Valentine", "F. Lynn", "F. Patek", 
	"G. Allenson", "G. Borgman", "G. Hubbard", "G. Matthews", 
	"G. Pryor", "G. Richards", "G. Roenick", "G. Tenace (76-77)", 
	"G. Tenace (82-83)", "G. Ward", "I. DeJesus", "J. Beniquez", 
	"J. Burroughs (81-82)", "J. Clark", "J. Dwyer", "J. Essian", 
	"J. Gantner", "J. Grubb", "J. Johnstone", "J. Leonard", 
	"J. Morales", "J. Morgan (79-80)", "J. Morgan (83-84)", "J. Orta", 
	"J. Quirk (82-83)", "J. Quirk (88-89)", "J. Royster", 
	"J. Royster (86-87)", "J. Royster (87-88)", "J. Rudi (76-77)", 
	"J. Rudi (81-82)", "J. Turner", "J. Wohlford", 
	"J. Youngblood (82-83)", "J. Youngblood (88-89)", "Jose Cruz", 
	"K. Gibson", "L. Aguayo", "L. Biittner", "L. Bostock", "L. Hisle", 
	"L. Lacy", "L. Parrish", "L. Randle (79-80)", "L. Randle (80-81)", 
	"L. Sakata", "Lamar Johnson", "Lee May", "M. Belanger", 
	"M. Cubbage", "M. Dilone", "M. Jorgensen", "M. Lum", "M. O'Berry", 
	"M. Trillo (83-84)", "M. Trillo (88-89)", "Marc Hill", 
	"Mike Davis", "Milt May", "O. Gamble (77-78)", "O. Gamble (84-85)",
	"O. Moreno", "P. Garner", "P. Kellogg", "P. Rose (78-79)", 
	"P. Rose (83-84)", "R. Burleson", "R. Dempsey", "R. Hebner", 
	"R. Howell", "R. Jackson (76-77)", "R. Jackson (81-82)", 
	"R. Jackson (86-87)", "R. Kittle (87-88)", "R. Kittle (88-89)", 
	"R. Knight", "R. LeFlore", "R. Leach", "R. Miller", "R. Office", 
	"R. Picciolo", "R. Smith", "R. Staub", "R. Stennett", "R. Wilfong",
	"R. Zisk", "Ron Jackson", "Ruppert Jones", "S. Bando", "S. Garvey",
	"S. Henderson (84-85)", "S. Lezcano", "S. Nicosia", "S. Sax", 
	"Steve Henderson(87-88", "T. Blackwell", "T. Fuentes", "T. Perez", 
	"T. Poquette", "U.L. Washington", "V. Law", "W. Horton", 
	"W. McCovey", "W. Nordhagen", "W. Randolph"), class = "factor"), 
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	95, 20, 52, 36, 2, 51, 67, 27, 14, 5, 42, 16, 6, 53, 89), runnext
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"funds"<-
structure(.Data = list(fund = structure(.Data = c(17, 43, 95, 84, 118, 32, 
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	"Dean Witter WrldWide", "Delaware", "Delaware Decatur I", 
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	"Dreyfus Appreciation", "Dreyfus Capital Grow", 
	"Dreyfus New Leaders", "Eaton Vance Investor", 
	"EuroPacific Growth", "Evergreen", "Evergreen Total Ret", 
	"FPA Paramount", "Fidelity", "Fidelity Advisor", 
	"Fidelity Balanced", "Fidelity Capital App", "Fidelity Equity Inc",
	"Fidelity Europe", "Fidelity Growth Co.", "Fidelity OTC", 
	"Fidelity Overseas", "Fidelity Puritan", "Fidelity Retire Grwt", 
	"Financial Dynamics", "Financial Ind Income", 
	"Financial Industrial", "First Investors Glob", 
	"Founders Blue Chip", "Founders Special", "Franklin Growth", 
	"Franklin Rising Div", "Fundamental Investor", 
	"G.T. Europe Growth A", "G.T. Int. Growth A", 
	"G.T. Pacific GrowthA", "George Putnam Bost A", "Gintel", 
	"Gradison-McDnld EV", "Guardian Park Avenue", 
	"Harbor International", "Hartwell EmergngGrwt", "IDEX 3", 
	"IDS Discovery", "IDS International", "IDS Mutual", 
	"IDS Progressive", "IDS Strategy Aggr Eq", "IDS Strategy Equity", 
	"International Equity", "Investment Co. Amer.", "Janus", 
	"Janus Venture", "John Hancock Sovergn", "Kaufmann", 
	"Kemper International", "Kemper Inv. Tot. Ret", 
	"Kemper Small Cap.Equ", "Kemper Total Return", 
	"Keystone Custodian", "Keystone Custodn S-4", 
	"Legg Mason Spec. Inv", "Lindner", "MFS Emerging Growth", 
	"MFS Lifetime EmrGrw", "MFS Lifetime Total R", "MFS Total Return", 
	"MainStay Total Ret.", "Mas Inv Growth Stock", "Mass Investors", 
	"Merl Lnch Strateg B", "Merrill Lynch BalInB", 
	"Merrill Lynch BasicV", "Merrill Lynch Cap A", 
	"Merrill Lynch Euro B", "Merrill Lynch Intl A", 
	"Merrill Lynch PacfcA", "MetLife StateStCapAp", 
	"National Total Retur", "Natl Inc & Growth A", "New Economy", 
	"New Perspective", "Newberger&Berman Grd", "Nicholas II", 
	"Nicholas Ltd. Editio", "Oppenheimer Discover", 
	"Oppenheimer EqutyInc", "Oppenheimer Global", "Oppenheimer Target",
	"Pacific Horizon AG", "Pax World", "Pennsylvania Mutual", 
	"Phoenix Balanced", "Pilgrim MagnaCap", "Pioneer Three", 
	"Prud Growth Opport B", "Prudential Equ Inc B", 
	"Prudential Equity B", "Prudential Global B", "Putnam Fund G&I A", 
	"Putnam Global Growth", "Putnam Managed Incom", 
	"Putnam OTC Emerg Grw", "Putnam Strategic Inc", "Putnam Vista", 
	"Putnam Voyager", "Rightime", "Rightime Blue Chip", 
	"Roberts. Steph. EmGr", "Royce Value", "SAFECO Growth", 
	"SAFECO Income", "Scudder Development", "Scudder Global", 
	"Scudder Internationa", "Security Action", "Selected Amer Shares", 
	"Seligman Capital", "Seligman Common Stck", "Shearson Aggr Growth",
	"Shearson Premium", "Shearson Sector An B", 
	"Sit \"New Beginning\"", "Skyline Special Equi", 
	"Smith Barney I & G A", "Stagecoach Corporate", "SteinRoe Special",
	"SteinRoe Stock", "SteinRoe Total Retur", "Strong Discovery", 
	"Strong Investment", "Strong Total Return", "T. Rowe Price OTC", 
	"T.Rowe Price EquInc", "T.Rowe Price G & I", 
	"T.Rowe Price Intl St", "T.Rowe Price New Hor", 
	"Templeton Foreign", "Templeton Growth", "Templeton SmallCo.Gr", 
	"Templeton World", "Thomson OpportunityB", "USAA Inv Cornerstone", 
	"USAA Mutual Aggr Grw", "USAA Mutual Inc Stck", 
	"United Contnentl Inc", "United Income", "United Intl. Growth", 
	"United New Concepts", "Value Line Lever Grt", "Vanguard Explorer",
	"Vanguard Ind Ext Mkt", "Vanguard Quantitativ", "Vanguard STAR", 
	"Vanguard Small CapSt", "Vanguard World IntGr", 
	"Vista Growth & Incom", "Wellington"), class = "factor"), type = 
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"geyser1"<-
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"geyser2"<-
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"health"<-
structure(.Data = list(state = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 8, 
	9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 25, 24, 
	26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42,
	43, 46, 45, 44, 47, 49, 48, 50), .Label = c("Alabama", "Alaska", 
	"Arizona", "Arkansas", "California", "Colorado", "Connecticut", 
	"Delaware", "Florida", "Georgia", "Hawaii", "Idaho", "Illinois", 
	"Indiana", "Iowa", "Kansas", "Kentucky", "Louisiana", "Maine", 
	"Maryland", "Massachusetts", "Michigan", "Minnesota", 
	"Mississippi", "Missouri", "Montana", "Nebraska", "Nevada", 
	"New Hampshire", "New Jersey", "New Mexico", "New York", 
	"North Carolina", "North Dakota", "Ohio", "Oklahoma", "Oregon", 
	"Pennslyvania", "Rhode Island", "South Carolina", "South Dakota", 
	"Tennessee", "Texas", "Utah", "Vermont", "Virginia", "Washington", 
	"West Virginia", "Wisconsin", "Wyoming"), class = "factor"), 
	region = structure(.Data = c(2, 6, 4, 9, 6, 4, 5, 7, 7, 7, 6, 4, 1,
	1, 8, 8, 2, 9, 5, 7, 5, 1, 8, 8, 2, 4, 8, 4, 5, 3, 4, 3, 7, 8, 1, 
	9, 6, 3, 5, 7, 8, 2, 9, 7, 5, 4, 6, 1, 7, 4), .Label = c(
	"East North Central", "East South Central", "Middle Atlantic", 
	"Mountain", "North East", "Pacific", "South Atlantic", 
	"West North Central", "West South Central"), class = "factor"), 
	reg = c(5, 9, 8, 6, 9, 8, 1, 3, 3, 3, 9, 8, 4, 4, 7, 7, 5, 6, 1, 3,
	1, 4, 7, 7, 5, 8, 7, 8, 1, 2, 8, 2, 3, 7, 4, 6, 9, 2, 1, 3, 7, 5, 
	6, 3, 1, 8, 9, 4, 3, 8), hlthspnd = c(1833, 1801, 1712, 1673, 1914,
	1807, 2080, 2028, 2037, 1884, 1889, 1234, 1840, 1738, 1657, 1727, 
	1713, 1960, 1592, 1918, 2402, 1856, 1969, 1983, 1440, 1440, 1754, 
	1771, 1735, 1887, 1582, 2134, 1631, 2083, 1859, 1553, 1573, 2105, 
	1916, 1558, 1736, 2009, 1742, 1722, 1454, 1434, 1691, 1762, 1832, 
	1301), pctpci = c(11.8, 8.2, 10.4, 11.3, 9.1, 9.3, 8, 10, 10.8, 
	10.8, 8.9, 8, 8.8, 10.1, 9.5, 9.3, 11, 12.9, 9.2, 8.7, 10.5, 9.9, 
	10.3, 11.1, 10.8, 9, 9.8, 9.2, 8.3, 7.4, 10.7, 9.5, 9.8, 12.9, 
	10.4, 9.8, 8.9, 11, 8.7, 10.1, 10.6, 12.3, 10.1, 8.6, 8.2, 9.9, 
	8.7, 9.8, 12.9, 7.6)), class = "data.frame", row.names = c("1", 
	"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
	"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
	"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
	"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
	"47", "48", "49", "50"))
"hockey1"<-
structure(.Data = list(team = structure(.Data = c(16, 1, 4, 17, 5, 10, 22, 
	21, 3, 23, 8, 12, 24, 11, 2, 19, 15, 9, 13, 6, 7, 20, 18, 14), 
	.Label = c("Boston Bruins", "Buffalo Sabres", "Calgary Flames", 
	"Chicago Blackhawks", "Detroit Red Wings", "Edmonton Oilers", 
	"Hartford Whalers", "Los Angeles Kings", "Minnesota North Stars", 
	"Montreal Canadiens", "New Jersey Devils", "New York Islanders", 
	"New York Rangers", "Ottawa Senators", "Philadelphia Flyers", 
	"Pittsburgh Penguins", "Quebec Nordiques", "San Jose Sharks", 
	"St. Louis Blues", "Tampa Bay Lightning", "Toronto Maple Leafs", 
	"Vancouver Canucks", "Washington Capitals", "Winnipeg Jets"), 
	class = "factor"), points = c(119, 109, 106, 104, 103, 102, 101, 
	99, 97, 93, 88, 87, 87, 87, 86, 85, 83, 82, 79, 60, 58, 53, 24, 24
	), gf = c(367, 332, 279, 351, 369, 326, 346, 288, 322, 325, 338, 
	335, 322, 309, 335, 282, 319, 272, 304, 242, 284, 245, 218, 202), 
	ga = c(268, 268, 230, 300, 280, 280, 278, 241, 282, 286, 340, 298, 
	320, 299, 297, 278, 319, 293, 308, 337, 369, 332, 414, 395)), 
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20", "21", "22", "23", "24"))
"hockey2"<-
structure(.Data = list(team = structure(.Data = c(7, 16, 3, 8, 11, 23, 22, 
	1, 13, 19, 6, 14, 4, 18, 17, 20, 10, 9, 21, 2, 12, 13, 7, 11, 1, 
	10, 2, 14, 16, 18, 23, 21, 3, 17, 19, 4, 22, 9, 8, 20, 6, 5, 4, 1, 
	6, 14, 11, 19, 20, 17, 10, 15, 16, 9, 11, 4, 20, 6, 1, 14, 6, 11, 
	1, 4, 20, 14, 6, 1, 20, 11, 4, 14), .Label = c("Boston Bruins", 
	"Buffalo Sabres", "Calgary Flames", "Chicago Black Hawks", 
	"Colorado Rockies", "Detroit Red Wings", "Edmonton Oilers", 
	"Hartford Whalers", "Los Angeles Kings", "Minnesota North Stars", 
	"Montreal Canadiens", "New Jersey Devils", "New York Islanders", 
	"New York Rangers", "Oakland Golden Seals", "Philadelphia Flyers", 
	"Pittsburgh Penguins", "Quebec Nordiques", "St. Louis Blues", 
	"Toronto Maple Leafs", "Vancouver Canucks", "Washington Capitals", 
	"Winnipeg Jets"), class = "factor"), points = c(106, 100, 95, 93, 
	92, 88, 86, 85, 82, 79, 78, 76, 72, 72, 72, 70, 70, 70, 66, 64, 64,
	118, 111, 109, 96, 94, 93, 92, 87, 82, 80, 77, 75, 75, 72, 72, 65, 
	63, 60, 56, 54, 49, 99, 99, 95, 92, 92, 86, 71, 64, 60, 58, 58, 38,
	90, 82, 79, 74, 48, 47, 90, 75, 69, 69, 67, 50, 61, 57, 53, 50, 49,
	30), gf = c(372, 310, 318, 287, 277, 279, 285, 301, 279, 281, 260, 
	307, 290, 267, 297, 286, 296, 318, 282, 280, 293, 385, 417, 360, 
	323, 346, 307, 316, 325, 356, 319, 290, 334, 310, 315, 332, 319, 
	314, 264, 298, 270, 241, 250, 277, 246, 246, 244, 224, 222, 182, 
	224, 169, 197, 168, 239, 240, 208, 221, 174, 195, 222, 155, 152, 
	169, 156, 152, 169, 195, 198, 181, 179, 161), ga = c(284, 245, 289,
	270, 241, 271, 278, 276, 281, 293, 274, 323, 310, 276, 290, 319, 
	314, 341, 314, 308, 368, 250, 295, 223, 285, 288, 273, 306, 313, 
	345, 332, 286, 345, 337, 349, 363, 338, 369, 351, 380, 351, 362, 
	170, 216, 199, 189, 201, 179, 242, 238, 257, 243, 225, 290, 173, 
	187, 187, 194, 275, 261, 133, 148, 172, 175, 167, 211, 124, 176, 
	159, 191, 180, 253), team = c(1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 
	1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 1982, 
	1982, 1982, 1982, 1970, 1970, 1970, 1970, 1970, 1970, 1970, 1970, 
	1970, 1970, 1970, 1970, 1966, 1966, 1966, 1966, 1966, 1966, 1953, 
	1953, 1953, 1953, 1953, 1953, 1943, 1943, 1943, 1943, 1943, 1943)),
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", 
	"29", "30", "31", "32", "33", "34", "35", "36", "37", "38", "39", 
	"40", "41", "42", "43", "44", "45", "46", "47", "48", "49", "50", 
	"51", "52", "53", "54", "55", "56", "57", "58", "59", "60", "61", 
	"62", "63", "64", "65", "66", "67", "68", "69", "70", "71", "72"))
"liinc"<-
structure(.Data = list(community = structure(.Data = c(1, 2, 3, 4, 5, 6, 7,
	8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
	25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
	42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58,
	59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 69, 72, 73, 74, 76,
	77, 75, 78, 79, 80, 81, 82, 83, 84, 86, 87, 88, 89, 85, 90, 91, 92,
	93, 94, 95, 96, 97, 99, 98, 100, 101, 102, 103, 104, 105, 106, 107,
	108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 
	121, 122, 123, 124, 125, 126, 127, 128, 129, 130, 131, 132, 133, 
	134, 135, 136, 137, 138, 139, 140, 141, 142, 143, 144, 145, 146, 
	147, 148, 149, 150, 151, 152, 153, 154, 155, 156, 157, 158, 159, 
	160, 161, 162, 163, 164, 165, 166, 167, 168, 169, 170, 171, 172, 
	173, 174, 175, 176, 177, 178, 180, 181, 179, 182, 183, 185, 184, 
	186, 187, 188, 189, 190, 191, 192, 193, 194, 195, 196, 198, 199, 
	200, 197, 201, 202, 203, 204, 205, 206, 207, 208, 209, 210, 211, 
	212, 213, 214, 215, 216, 217, 218, 219, 220, 221, 222, 223, 224, 
	225, 226, 227, 228, 229, 230, 231, 232, 233, 234, 235, 236, 237, 
	238, 257, 239, 240, 241, 242, 243, 244, 245, 246, 247, 248, 249, 
	250, 251, 252, 253, 254, 255, 256), .Label = c("Albertson", 
	"Amagansett", "Amityville", "Asharoken", "Atlantic Beach", 
	"Babylon Village", "Baldwin", "Baldwin Harbor", "Barnum Island", 
	"Baxter Estates", "Bay Shore", "Bayport", "Bayville", "Baywood", 
	"Belle Terre", "Bellerose", "Bellmore", "Bellport", "Bethpage", 
	"Blue Point", "Bohemia", "Brentwood", "Bridgehampton", 
	"Brightwaters", "Brookhaven", "Brookville", "Calverton", 
	"Carle Place", "Cedarhurst", "Center Moriches", "Centereach", 
	"Centerport", "Central Islip", "Centre Island", 
	"Cold Spring Harbor", "Commack", "Copiague", "Coram", "Cove Neck", 
	"Cutchogue", "Deer Park", "Dering Harbor", "Dix Hills", 
	"East Farmingdale", "East Hampton Village", "East Hills", 
	"East Islip", "East Massapequa", "East Meadow", "East Moriches", 
	"East Northport", "East Norwich", "East Patchogue", "East Quogue", 
	"East Rockaway", "East Shoreham", "East Williston", "Eatons Neck", 
	"Elmont", "Elwood", "Farmingdale", "Farmingville", "Flanders", 
	"Floral Park", "Flower Hill", "Fort Salonga", "Franklin Square", 
	"Freeport", "Garden City", "Garden City Park", "Garden City South",
	"Glen Cove City", "Glen Head", "Glenwood Landing", "Great Neck", 
	"Great Neck Estates", "Great Neck Plaza", "Greenlawn", "Greenport",
	"Greenport West", "Halesite", "Hampton Bays", "Hauppauge", 
	"Head of the Harbor", "Helwett Harbor", "Hempstead Village", 
	"Herricks", "Hewlett", "Hewlett Bay Park", "Hewlett Neck", 
	"Hicksville", "Holbrook", "Holtsville", "Huntington", 
	"Huntington Bay", "Huntington Station", "Inwood", "Island Park", 
	"Islandia", "Islip", "Islip Terrace", "Jamesport-Aquebogue", 
	"Jericho", "Kensington", "Kings Park", "Kings Point", "Lake Grove",
	"Lake Ronkonkoma", "Lake Success", "Lakeview", "Lattingtown", 
	"Laurel", "Laurel Hollow", "Lawrence", "Levittown", "Lido Beach", 
	"Lindenhurst", "Lloyd Harbor", "Locust Valley", "Long Beach City", 
	"Lynbrook", "Malverne", "Manhasset", "Manhasset Hills", 
	"Manorhaven", "Manorville", "Massapequa", "Massapequa Park", 
	"Mastic", "Mastic Beach", "Matinecock", "Mattituck", "Medford", 
	"Melville", "Merrick", "Middle Island", "Mill Neck", 
	"Miller Place", "Mineola", "Montauk", "Mount Sinai", "Munsey Park",
	"Muttontown", "Nesconset", "New Cassel", "New Hyde Park", 
	"Nissequogue", "North Amityville", "North Babylon", 
	"North Bay Shore", "North Bellmore", "North Bellport", 
	"North Great River", "North Haven", "North Hills", 
	"North Lindenhurst", "North Massapequa", "North Merrick", 
	"North New Hyde Park", "North Patchogue", "North Valley Stream", 
	"North Wantagh", "Northport", "Northwest Harbor", 
	"Noyack-Water Mill", "Oakdale", "Ocean Beach", "Oceanside", 
	"Old Bethpage", "Old Brookville", "Old Field", "Old Westbury", 
	"Oyster Bay", "Oyster Bay Cove", "Patchogue", "Peconic", 
	"Plainedge", "Plainview", "Plandome", "Plandome Heights", 
	"Plandome Manor", "Poospatuck", "Poquott", "Port Jefferson", 
	"Port Jefferson Station", "Port Washington", 
	"Port Washington North", "Quogue", "Remsenburg-Speonk", "Ridge", 
	"Riverhead", "Riverside-Pine Valley", "Rockville Centre", 
	"Rocky Point", "Ronkonkoma", "Roosevelt", "Roslyn", 
	"Roslyn Estates", "Roslyn Harbor", "Roslyn Heights", 
	"Russell Gardens", "Saddle Rock", "Sag Harbor", "Salisbury", 
	"Saltaire", "Sands Point", "Sayville", "Sea Cliff", "Seaford", 
	"Searingtown", "Selden", "Setauket-East Setauket", 
	"Shelter Island", "Shelter Island Heights", "Shinnecock", 
	"Shinnecock Hills", "Shirley", "Shoreham", "Smithtown", 
	"Sound Beach", "South Farmingdale", "South Floral Park", 
	"South Hempstead", "South Huntington", "South Valley Stream", 
	"Southampton", "Southold", "Springs", "St. James", "Stewart Manor",
	"Stony Brook", "Syosset", "Terryville", "Thomaston", "Uniondale", 
	"University Gardens", "Upper Brookville", "Valley Stream", 
	"Wading River", "Wantagh", "West Babylon", "West Bay Shore", 
	"West Hempstead", "West Hills", "West Islip", "West Sayville", 
	"Westbury", "Westhampton", "Westhampton Beach", "Wheatley Heights",
	"Williston Park", "Woodbury", "Woodmere", "Woodsburgh", 
	"Wyandanch", "Yaphank", "Village of the Branch"), class = "factor"), 
	income79 = c(47838, 27919, 39294, 95159, 54167, 41908, 44383, 
	54304, 42275, 48242, 20872, 41545, 43192, 40248, 74205, 56255, 
	46880, 46755, 46698, 38715, 36278, 39489, 30897, 52590, 44676, 
	105979, 17818, 39799, 41218, 32597, 41695, 44260, 34706, 67170, 
	58245, 53188, 37987, 40422, 65621, 32344, 42777, 133502, 63256, 
	36567, 35696, 94865, 39858, 48818, 46948, 36116, 46234, 55442, 
	34087, 29991, 41339, 54068, 63039, 64384, 38101, 51223, 37368, 
	38174, 17969, 41408, 91748, 57503, 39468, 35545, 44954, 43642, 
	64929, 40050, 43145, 51481, 92975, 33364, 53968, 45851, 18856, 
	34025, 56880, 28234, 46351, 70098, 30232, 50118, 44557, 133502, 
	133502, 125802, 45716, 40968, 40981, 50020, 87354, 38717, 21912, 
	43773, 30303, 38838, 40217, 37035, 62982, 104123, 45000, 128856, 
	37864, 36857, 92065, 45767, 64197, 40050, 89470, 66001, 45378, 
	53672, 37330, 100734, 41773, 29028, 40520, 49555, 53884, 78316, 
	39174, 31830, 48238, 51819, 29911, 19671, 66919, 37257, 39849, 
	60374, 54885, 32980, 75200, 46341, 39235, 28825, 42962, 87978, 
	89945, 44381, 36122, 41070, 72610, 31862, 43354, 37821, 48188, 
	30077, 43048, 35956, 92195, 38177, 49899, 48375, 45433, 34137, 
	46029, 51317, 42821, 31668, 30424, 43268, 28480, 48548, 56948, 
	97368, 76987, 98699, 37227, 100385, 20968, 30340, 45522, 56729, 
	74425, 107092, 93762, NA, 38359, 37416, 45445, 48622, 52389, 40235,
	33724, 28863, 20118, 12408, 46150, 21851, 37802, 38768, 109840, 
	90052, 52875, 41794, 88509, 102103, 27378, 51266, 133502, 133502, 
	39082, 42983, 47627, 80207, 35351, 49285, 22099, 33603, 29096, 
	29427, 32019, 57455, 50080, 35677, 48259, 41225, 46659, 45118, 
	57740, 33014, 31869, 27469, 42316, 49212, 53234, 56882, 42462, 
	58001, 39828, 51387, 92558, 42004, 57288, 37197, 50189, 38671, 
	48836, 45481, 57615, 45810, 38286, 46554, 28614, 35563, 51405, 
	43868, 66038, 66732, 105305, 29614, 32873), income89 = c(49676, 
	34705, 46442, 84064, 72812, 52023, 53994, 63421, 60709, 58031, 
	37702, 54368, 55511, 46528, 100000, 73990, 58203, 53062, 52533, 
	52044, 47241, 48665, 41397, 66935, 47903, 98700, 21152, 47111, 
	52119, 42737, 50224, 58544, 42434, 82969, 76608, 62014, 45738, 
	49135, 112114, 42766, 48117, 125000, 79154, 48125, 46771, 111521, 
	52796, 57717, 54511, 48361, 52108, 67814, 41052, 33607, 50818, 
	64725, 72678, 71520, 44452, 63700, 46667, 47354, 37271, 51344, 
	107582, 68464, 46186, 43948, 51553, 45625, 74478, 42982, 53746, 
	60775, 117706, 46316, 60567, 52601, 25563, 30926, 64745, 35736, 
	57959, 86135, 36715, 56231, 60554, 150001, 150001, 150001, 50794, 
	51211, 51400, 62121, 98626, 45775, 27595, 52238, 45020, 50459, 
	51796, 36867, 75043, 110522, 53155, 140838, 48164, 45485, 97095, 
	50279, 94557, 36953, 133460, 78815, 52866, 77279, 46615, 130720, 
	50145, 41495, 45453, 60310, 66902, 81445, 43239, 39683, 60345, 
	58773, 39512, 35776, 97155, 36415, 50190, 72581, 65383, 41103, 
	88030, 60162, 44635, 31849, 57535, 108553, 119981, 60204, 48314, 
	47023, 87852, 35694, 51976, 47275, 56075, 37722, 56911, 37308, 
	110711, 49025, 55273, 60233, 51987, 45874, 53618, 55488, 57733, 
	41558, 38117, 57291, 26250, 53875, 62308, 116731, 103403, 137518, 
	47679, 150001, 34173, 42031, 57071, 66095, 73948, 130183, 110644, 
	20781, 62216, 47873, 54620, 64224, 61722, 52031, 51303, 31878, 
	28491, 19671, 55476, 37974, 47748, 43559, 118093, 105326, 63013, 
	53337, 87032, 113346, 35952, 57580, 25714, 134484, 53806, 46672, 
	55259, 85337, 46298, 66727, 37159, 41339, 29464, 31735, 41602, 
	77959, 61455, 44944, 54437, 44453, 57218, 54865, 59080, 38770, 
	36288, 41754, 51571, 63545, 63244, 65806, 54131, 63393, 46917, 
	64187, 128993, 47287, 68998, 51838, 60134, 47067, 54947, 52271, 
	67805, 57081, 49028, 52114, 41806, 42143, 57495, 50496, 91102, 
	79623, 91909, 34421, 44569)), class = "data.frame", row.names = c(
	"1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", 
	"13", "14", "15", "16", "17", "18", "19", "20", "21", "22", "23", 
	"24", "25", "26", "27", "28", "29", "30", "31", "32", "33", "34", 
	"35", "36", "37", "38", "39", "40", "41", "42", "43", "44", "45", 
	"46", "47", "48", "49", "50", "51", "52", "53", "54", "55", "56", 
	"57", "58", "59", "60", "61", "62", "63", "64", "65", "66", "67", 
	"68", "69", "70", "71", "72", "73", "74", "75", "76", "77", "78", 
	"79", "80", "81", "82", "83", "84", "85", "86", "87", "88", "89", 
	"90", "91", "92", "93", "94", "95", "96", "97", "98", "99", "100", 
	"101", "102", "103", "104", "105", "106", "107", "108", "109", 
	"110", "111", "112", "113", "114", "115", "116", "117", "118", 
	"119", "120", "121", "122", "123", "124", "125", "126", "127", 
	"128", "129", "130", "131", "132", "133", "134", "135", "136", 
	"137", "138", "139", "140", "141", "142", "143", "144", "145", 
	"146", "147", "148", "149", "150", "151", "152", "153", "154", 
	"155", "156", "157", "158", "159", "160", "161", "162", "163", 
	"164", "165", "166", "167", "168", "169", "170", "171", "172", 
	"173", "174", "175", "176", "177", "178", "179", "180", "181", 
	"182", "183", "184", "185", "186", "187", "188", "189", "190", 
	"191", "192", "193", "194", "195", "196", "197", "198", "199", 
	"200", "201", "202", "203", "204", "205", "206", "207", "208", 
	"209", "210", "211", "212", "213", "214", "215", "216", "217", 
	"218", "219", "220", "221", "222", "223", "224", "225", "226", 
	"227", "228", "229", "230", "231", "232", "233", "234", "235", 
	"236", "237", "238", "239", "240", "241", "242", "243", "244", 
	"245", "246", "247", "248", "249", "250", "251", "252", "253", 
	"254", "255", "256", "257"))
"lischool"<-
structure(.Data = list(district = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 
	8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
	25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
	42, 43, 44, 45, 46, 47, 48, 49, 52, 50, 51, 53, 54, 55, 56), 
	.Label = c("Baldwin", "Bellmore", "Bellmore - Merrick", "Bethpage",
	"Carle Place", "East Meadow", "East Rockaway", "East Williston", 
	"Elmont", "Farmingdale", "Floral Park", "Franklin Square", 
	"Freeport", "Garden City", "Glen Cove", "Great Neck", "Hempstead", 
	"Herricks", "Hewlett Woodmere", "Hicksville", "Island Park", 
	"Island Trees", "Jericho", "Lawrence", "Levittown", 
	"Locust Valley", "Long Beach", "Lynbrook", "Malverne", "Manhasset",
	"Massapequa", "Merrick", "Mineola", "New Hyde Park", 
	"North Bellmore", "North Merrick", "North Shore", "Oceanside", 
	"Oyster Bay - East Norwich", "Plainedge", 
	"Plainview - Old Bethpage", "Port Washington", "Rockville Centre", 
	"Roosevelt", "Roslyn", "Seaford", "Sewanhaka", "Syosset", 
	"Uniondale", "Valley Stream 13", "Valley Stream 24", 
	"Valley Stream 30", "Valley Stream Central", "Wantagh", 
	"West Hempstead", "Westbury"), class = "factor"), legislat = c(5, 
	19, 19, 17, 11, 13, 6, 11, 3, 14, 8, 3, 1, 8, 18, 10, 2, 11, 7, 17,
	7, 15, 17, 4, 15, 18, 4, 6, 8, 9, 12, 19, 11, 9, 13, 13, 18, 7, 17,
	14, 16, 10, 5, 1, 10, 19, 3, 16, 1, 6, 6, 6, 6, 13, 8, 2), enroll
	 = c(4658, 950, 4706, 2460, 1439, 7446, 1131, 1377, 3301, 5400, 
	1544, 1577, 6099, 2977, 2928, 5383, 5418, 3432, 2803, 4498, 819, 
	2117, 2033, 3680, 6569, 1917, 4149, 2517, 1817, 2253, 6678, 1659, 
	2659, 1282, 1969, 1143, 1985, 5235, 1287, 2820, 4239, 3676, 3170, 
	2975, 2468, 2280, 6388, 5176, 4811, 1199, 2003, 906, 3336, 2703, 
	2184, 2927), white = c(3549, 912, 4470, 2300, 1273, 6612, 1063, 
	1232, 1472, 4649, 1386, 1395, 1713, 2783, 1730, 4370, 21, 2416, 
	2522, 3580, 714, 1951, 1787, 2693, 6174, 1748, 2626, 2303, 728, 
	1793, 6517, 1605, 2191, 1025, 1825, 1048, 1855, 4858, 1096, 2693, 
	4018, 2598, 2634, 8, 2001, 2191, 4343, 4415, 437, 974, 1826, 782, 
	2842, 2602, 1799, 201)), class = "data.frame", row.names = c("1", 
	"2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", "13", 
	"14", "15", "16", "17", "18", "19", "20", "21", "22", "23", "24", 
	"25", "26", "27", "28", "29", "30", "31", "32", "33", "34", "35", 
	"36", "37", "38", "39", "40", "41", "42", "43", "44", "45", "46", 
	"47", "48", "49", "50", "51", "52", "53", "54", "55", "56"))
"mort"<-
structure(.Data = list(lender = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 8,
	9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20), .Label = c(
	"Anchor Savings", "Bank of the Hamptons", "Bay Ridge Federal", 
	"Brooklyn Federal", "Chemical Bank", "Citibank", 
	"Columbia Federal", "Countrywide Funding", "Dale Mortgage Bankers",
	"EAB", "East NY Savings Bank", "Fairmont Funding", "GMAC Mortgage",
	"Home Federal Savings", "Maspeth Federal", "Ridgewood Savings", 
	"Roosevelt Savings", "Roslyn Savings Bank", "The Mortgage Corner", 
	"Triumphe Financial"), class = "factor"), type = c(0, 0, 1, 1, 0, 
	0, 0, 0, 0, 1, 1, 0, 1, 0, 0, 1, 0, 0, 0, 0), rate = c(7.875, 
	7.125, 5, 4.5, 7.5, 7.125, 7.5, 7.5, 6.75, 6, 5.25, 7.25, 4.25, 
	7.25, 8, 4.5, 8, 6.875, 7.375, 6.875), points = c(0, 1.5, 2, 1.5, 
	2, 2, 2, 0, 2.75, 1.75, 0, 3.5, 2.5, 2, 0, 2, 0, 2, 2, 2.25)), 
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20"))
"nba"<-
structure(.Data = list(name = structure(.Data = c(78, 65, 23, 40, 69, 12, 
	42, 32, 90, 91, 71, 77, 60, 100, 64, 45, 51, 68, 80, 59, 92, 54, 
	47, 43, 19, 98, 15, 6, 30, 61, 49, 48, 50, 53, 29, 34, 89, 74, 105,
	11, 62, 1, 21, 10, 82, 5, 58, 103, 25, 73, 41, 93, 17, 76, 35, 3, 
	55, 4, 66, 99, 2, 33, 39, 24, 31, 75, 104, 46, 28, 63, 95, 20, 102,
	79, 96, 86, 13, 27, 84, 16, 97, 88, 72, 101, 70, 26, 37, 9, 44, 36,
	87, 14, 85, 81, 52, 94, 18, 57, 56, 67, 38, 83, 22, 8, 7), .Label
	 = c("A. Bowie", "A. Johnson", "A. Peeler", "A. Robertson", 
	"B. Coles", "B. J. Armstrong", "B. Kimble", "B. Phills", 
	"B. Price", "B. Shaw", "B. Smith", "C. Drexler", "C. Smith", 
	"C. Williams", "D. Ainge", "D. Barros", "D. Brown", "D. Cooper", 
	"D. Harper", "D. Overton", "D. Rivers", "D. Walker", "D. West", 
	"D. Young", "E. Murdock", "F. Johnson", "G. Anthony", "G. Grant", 
	"G. Payton", "G. Wilkins", "H. Davis", "H. Hawkins", "H. Miner", 
	"I. Thomas", "J. Bagley", "J. Barry", "J. Battle", "J. Crotty", 
	"J. Dawkins", "J. Dumars", "J. Hamphries", "J. Hornacek", 
	"J. Jackson", "J. Les", "J. Malone", "J. Paxson", "J. Starks", 
	"J. Stockton", "K. Anderson", "K. Edwards", "K. Gill", 
	"K. Jennings", "K. Johnson", "K. Smith", "L. Daniels", "L. Green", 
	"L. Mayberry", "L. Smith", "L. Sprewell", "M. Abdul-Rauf", 
	"M. Adams", "M. Blaylock", "M. Cheeks", "M. Jackson", "M. Jordan", 
	"M. Macon", "M. Newbern", "M. Price", "M. Richmond", "M. Wiley", 
	"M. Williams", "N. Knight", "P. Richardson", "R. Blackman", 
	"R. Brown", "R. Chapman", "R. Harper", "R. Miller", "R. Pack", 
	"R. Pierce", "R. Robinson", "R. Strickland", "R. Woods", 
	"S. Brooks", "S. Douglas", "S. Floyd", "S. Green", "S. Henson", 
	"S. Marciulionis", "S. Skiles", "S. Smith", "S. Threatt", 
	"S. Webb", "T. Bennett", "T. Bogues", "T. Brandon", "T. George", 
	"T. Hardaway", "T. Legler", "T. Porter", "T. Smith", "T. Tucker", 
	"V. D. Negro", "V. Fleming", "V. Maxwell"), class = "factor"), 
	height = c(201, 198, 198, 191, 196, 201, 193, 191, 185, 203, 188, 
	198, 185, 191, 191, 193, 196, 183, 193, 196, 188, 191, 196, 198, 
	193, 183, 196, 188, 198, 178, 185, 185, 191, 185, 193, 185, 196, 
	198, 193, 196, 185, 198, 193, 198, 191, 188, 191, 193, 185, 185, 
	191, 170, 185, 193, 210, 193, 201, 193, 196, 193, 180, 196, 188, 
	193, 196, 191, 196, 188, 191, 188, 160, 191, 196, 188, 183, 191, 
	191, 188, 180, 180, 196, 185, 185, 193, 193, 185, 188, 185, 180, 
	196, 196, 188, 185, 188, 170, 183, 185, 185, 185, 193, 185, 183, 
	193, 196, 193), games = c(82, 78, 80, 76, 45, 49, 79, 81, 79, 48, 
	76, 81, 80, 81, 82, 79, 69, 75, 77, 77, 82, 82, 79, 28, 61, 66, 81,
	81, 81, 69, 55, 82, 40, 49, 82, 80, 30, 59, 72, 39, 80, 77, 77, 68,
	78, 80, 68, 74, 80, 74, 79, 69, 81, 60, 10, 76, 78, 69, 47, 33, 75,
	73, 74, 63, 50, 75, 74, 59, 74, 35, 82, 45, 68, 77, 82, 53, 79, 70,
	82, 70, 49, 54, 51, 55, 57, 78, 41, 68, 72, 46, 13, 35, 79, 79, 8, 
	74, 64, 81, 53, 33, 39, 40, 37, 31, 9), minutes = c(2954, 3067, 
	3104, 3094, 1728, 1671, 2860, 2977, 3036, 1610, 2661, 2970, 2710, 
	2883, 3117, 2558, 2430, 2380, 2218, 2741, 2893, 2422, 2477, 938, 
	2108, 2609, 2163, 2492, 2079, 2499, 2010, 2863, 1134, 1643, 2548, 
	2922, 836, 1434, 2251, 865, 2820, 1761, 1886, 1603, 2474, 2232, 
	1546, 1526, 2437, 2396, 2034, 2335, 2254, 1300, 97, 1656, 1573, 
	2006, 1141, 635, 2030, 1383, 1598, 836, 815, 1726, 1503, 1030, 
	1624, 510, 2833, 990, 909, 1579, 1622, 867, 1266, 1699, 1516, 1243,
	380, 719, 888, 752, 995, 1122, 497, 859, 881, 552, 81, 242, 1932, 
	1585, 136, 857, 645, 1503, 626, 311, 243, 174, 511, 139, 55), age
	 = c(28, 30, 26, 30, 28, 31, 30, 27, 29, 24, 27, 29, 24, 30, 28, 
	32, 25, 29, 34, 23, 32, 28, 28, 23, 32, 27, 34, 26, 30, 30, 23, 31,
	28, 27, 25, 32, 29, 34, 28, 23, 26, 30, 32, 27, 27, 25, 24, 27, 25,
	27, 31, 30, 25, 26, 33, 24, 26, 31, 24, 27, 28, 22, 30, 31, 23, 25,
	31, 33, 28, 37, 28, 24, 34, 24, 28, 33, 23, 26, 28, 26, 25, 25, 26,
	25, 27, 35, 31, 25, 30, 24, 23, 23, 27, 27, 25, 24, 24, 23, 23, 26,
	24, 23, 32, 24, 27), ppg = c(21.2, 32.6, 19.3, 23.5, 21.9, 19.9, 
	19.1, 20.3, 15.4, 16, 15.1, 18, 19.2, 18.2, 14.4, 18.1, 
	16.899999999999998, 18.2, 18.2, 15.4, 15.1, 13, 17.5, 16.3, 18.2, 
	21.5, 11.8, 12.3, 11.1, 14.8, 16.899999999999998, 15.1, 13.9, 
	16.100000000000002, 13.5, 17.600000000000002, 17.399999999999998, 
	9.7, 13.8, 8.9, 13.4, 8, 7.8, 7.3, 13.7, 10.6, 9.3, 7.4, 14.4, 
	10.4, 8.8, 14.5, 10.9, 12.5, 2.3, 10.4, 9.1, 9, 7.5, 8.8, 8.7, 
	10.3, 8.9, 2.9, 5.4, 7.6, 9.5, 4.2, 6.6, 3.6, 10, 8.1, 5.2, 10.5, 
	8.8, 6.6, 4.3, 6.6, 6.3, 7.8, 2.5, 4, 6.1, 6, 4.5, 4.3, 5.4, 3.9, 
	4.5, 4.4, 4.8, 2.3, 7.8, 8.4, 8.6, 3.7, 2.4, 5.2, 4.5, 3.6, 2.6, 
	1.7, 2.2, 3, 3.7), apg = c(3.2, 5.5, 2.9, 4, 4.9, 5.7, 6.9, 3.9, 
	9.4, 5.6, 8.7, 4.5, 4.2, 5.2, 8.8, 1.6, 3.9, 8, 2.9, 3.8, 6.9, 5.4,
	5.1, 4.7, 5.4, 10.6, 3.3, 4, 2.3, 7.5, 8.2, 12, 3, 7.8, 4.9, 8.5, 
	3.5, 2.6, 4.2, 1.3, 8.4, 2.3, 5.3, 3.5, 7.2, 4.6, 2.7, 4, 7.6, 7.7,
	4.1, 7, 5.8, 1.9, 2, 2.2, 1.9, 1.6, 2.6, 1.4, 7.5, 1, 4.6, 1.8, 
	1.7, 2.6, 3, 2.3, 4.8, 3.1, 8.8, 3.5, 1.2, 4.4, 3.7, 2.5, 2.5, 5.7,
	3, 2.2, 1.2, 2.9, 2.8, 1.1, 3.1, 2.4, 1.3, 2.3, 2.3, 1.4, 0.5, 
	0.69999999999999992, 6.4, 4, 2.9, 1.8, 2.3, 3.3, 2.2, 1.7, 1.4, 1, 
	1.4, 0.3, 0.4), rpg = c(3.1, 6.7, 3.1, 1.9, 3.4, 6.3, 4.3, 4.3, 
	3.7, 4.1, 3.6, 5.3, 2.8, 3.9, 4.7, 2.2, 4.9, 2.7, 2.5, 3.5, 3.3, 2,
	2.6, 4.4, 2, 4, 2.7, 1.8, 2.7, 3.4, 4.1, 2.9, 3, 2.1, 3.4, 2.9, 
	3.2, 1.7, 3.1, 3.2, 3.5, 2.5, 2.5, 3.8, 4.3, 2, 1.5, 2.2, 3.6, 3.6,
	1.8, 2.8, 3.1, 1.5, 0.69999999999999992, 2.3, 2.8, 3.9, 2.1, 1.8, 
	1.9, 2, 1.8, 0.69999999999999992, 1.1, 2.8, 2.3, 0.8, 1.9, 1.2, 
	3.7, 2.4, 1, 2.1, 2.2, 1.7, 1.2, 2.4, 1.2, 1.6, 0.6, 1, 1.2, 1.6, 
	1.6, 1.5, 0.69999999999999992, 1.5, 1.2, 0.9, 0.69999999999999992, 
	0.9, 2.1, 2, 1.4, 0.8, 0.8, 1.4, 0.69999999999999992, 1.1, 0.4, 
	0.3, 1.6, 0.5, 1.2), fgp = c(47.9, 49.5, 51.7, 46.6, 47.4, 42.9, 
	47, 47, 46.7, 45.1, 44.6, 45.1, 45, 45.4, 48.6, 49.4, 44.9, 48.4, 
	48.9, 46.4, 50.8, 52, 42.8, 39.5, 41.9, 44.7, 46.2, 49.9, 45.3, 
	43.9, 43.5, 48.6, 46.8, 49.9, 49.4, 41.8, 54.3, 44.3, 40.7, 44.6, 
	42.9, 47.1, 43.7, 39.3, 48.5, 46.4, 45.8, 50.7, 46.8, 47.9, 43.6, 
	43.3, 46.8, 47.7, 36, 46.8, 44.3, 45.8, 41.5, 43.6, 50.2, 47.5, 
	43.7, 41.3, 43.8, 46.3, 50.5, 45.1, 44.1, 54.8, 45.3, 47.1, 48.5, 
	47, 47.8, 40.7, 43.3, 41.5, 47.5, 45.1, 37.8, 39, 39.1, 48.4, 37.8,
	43.6, 41.5, 35.799999999999996, 42.5, 36.9, 50.9, 36.5, 49.8, 42.3,
	59.5, 42.3, 39.2, 45.6, 43.9, 37.2, 51.4, 34.799999999999996, 35.4,
	46.3, 42.4), ftp = c(88, 83.7, 84.1, 86.4, 84.5, 83.9, 86.5, 86, 
	89.2, 78.7, 90.7, 76.9, 93.5, 84.3, 80.3, 85.2, 77.2, 94.8, 88.9, 
	74.6, 82.3, 87.8, 79.5, 73.9, 75.6, 77.4, 84.8, 86.1, 84, 85.6, 
	77.6, 79.8, 84.4, 81.9, 77, 73.7, 76.1, 78.9, 71.900000000000008, 
	83.2, 72.8, 79.8, 82.1, 78.2, 71.7, 80.5, 85.8, 86.3, 78, 74.2, 
	77.7, 85.1, 79.3, 81, 83.3, 78.6, 72.7, 65.599999999999992, 70, 
	80.3, 79.1, 76.2, 79.6, 87.5, 79.6, 73.2, 72.6, 85, 74.3, 88.9, 
	83.3, 72.8, 81.8, 76.8, 82.5, 79.4, 79.2, 67.3, 83, 83.1, 83.3, 85,
	77.9, 75.6, 65.400000000000008, 77.6, 77.8, 79.4, 84, 67.3, 75, 
	81.8, 56, 57.4, 77.8, 73.2, 71.400000000000008, 57.4, 62.5, 56.7, 
	68.400000000000008, 73.1, 46.2, 60, 37.5)), class = "data.frame", 
	row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", 
	"11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", 
	"22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", 
	"33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", 
	"44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", 
	"55", "56", "57", "58", "59", "60", "61", "62", "63", "64", "65", 
	"66", "67", "68", "69", "70", "71", "72", "73", "74", "75", "76", 
	"77", "78", "79", "80", "81", "82", "83", "84", "85", "86", "87", 
	"88", "89", "90", "91", "92", "93", "94", "95", "96", "97", "98", 
	"99", "100", "101", "102", "103", "104", "105"))
"nyseotc"<-
structure(.Data = list(nasdaqret = c(-0.1053, 0.066699999999999992, 
	-0.071400000000000008, -0.0294, 0.0423, -0.016899999999999998, 
	-0.0182, -0.1092, 0.0192, -0.0707, -0.0396, -0.0381, 0.0459, 
	0.0038, 0.0156, -0.0541, 0.0078, -0.0398, 0.1176, 0.0057, 
	-0.032300000000000004, 0.0476, 0.1224, -0.039, -0.0563, -0.0139, 
	0.0172, -0.0423, -0.0221, -0.0081), nyseret = c(-0.0246, -0.0212, 
	0.0789, -0.025, -0.0208, -0.0299, 0.006, -0.029, 0.0435, 0.0891, 
	-0.0102, 0.0266, -0.049, -0.01, 0.0566, 0.063200000000000008, 
	0.0098, -0.027, -0.0252, 0.023, -0.0588, -0.0112, 0.0484, -0.0178, 
	0.025, -0.0185, 0.0062, 0.0057, 0.0112, 0.0026)), class = 
	"data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8",
	"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
	"20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30"))
"pcb"<-
structure(.Data = list(bay = structure(.Data = c(6, 18, 27, 4, 5, 22, 14, 
	37, 25, 13, 16, 24, 7, 33, 35, 36, 1, 20, 26, 19, 2, 28, 11, 30, 
	29, 12, 34, 31, 32, 3, 10, 8, 23, 9, 15, 17, 21), .Label = c(
	"Apalachicola Bay", "Barataria Bay", "Bodega Bay", "Boston Harbor",
	"Buzzards' Bay", "Casco Bay", "Charleston Harbor", 
	"Columbia River Mouth", "Commencement Bay", "Coos Bay", 
	"Corpus Christi Bay", "Dana Point", "Delaware Bay", 
	"E. Long Island Sound", "Elliott Bay", "Lower Chesapeake Bay", 
	"Lutak Inlet", "Merrimack River", "Mississippi R. Delta", 
	"Mobile Bay", "Nahku Bay", "Narragansett Bay", "Nisqually Beach", 
	"Pamilico Sound", "Raritan Bay", "Round Island", "Salem Harbor", 
	"San Antonio Bay", "San Diego Bay", "San Diego Harbor", 
	"San Pedro Canyon", "Santa Monica Bay", "Sapelo Sound", 
	"Seal Beach", "St. Johns River", "Tampa Bay", 
	"W. Long Island Sound"), class = "factor"), pcb84 = c(95.28, 52.97,
	533.58000000000008, 17104.86, 308.45999999999996, 159.96, 10, 
	234.43, 443.89, 2.5, 51, 0, 9.1, 0, 140, 0, 12, 0, 0, 34, 0, 0, 0, 
	422.1, 6.74, 7.06, 46.71, 159.56, 14, 4.18, 3.19, 8.77, 
	4.2300000000000008, 20.6, 20.6, 5.5, 6.6), pcb85 = c(77.55, 29.23, 
	403.1, 736, 192.15, 220.6, 8.62, 174.31, 529.28, 
	130.66999999999998, 39.74, 0, 8.43, 0, 120.04, 0, 11.93, 0, 0, 
	30.14, 0, 0, 0, 531.66999999999992, 9.3, 5.74, 46.47, 176.9, 13.69,
	4.89, 6.6, 6.7300000000000008, 4.28, 20.5, 20.5, 5.8, 5.08)), 
	class = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", 
	"7", "8", "9", "10", "11", "12", "13", "14", "15", "16", "17", 
	"18", "19", "20", "21", "22", "23", "24", "25", "26", "27", "28", 
	"29", "30", "31", "32", "33", "34", "35", "36", "37"))
"ppp"<-
structure(.Data = list(country = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 
	8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 
	25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41,
	42, 43, 44), .Label = c("Australia", "Austria", "Belgium", 
	"Canada", "Chile", "Colombia", "Costa Rica", "Cyprus", 
	"Czechoslovakia", "Denmark", "Ecuador", "Egypt", "Finland", 
	"France", "Germany", "Ghana", "Greece", "Hungary", "India", 
	"Indonesia", "Iran", "Ireland", "Israel", "Italy", "Japan", 
	"Korea", "Mexico", "Morocco", "Netherlands", "New Zealand", 
	"Norway", "Panama", "Philippines", "Singapore", "South Africa", 
	"Spain", "Sri Lanka", "Sweden", "Switzerland", "Thailand", 
	"Turkey", "United Kingdom", "Uruguay", "Venezuela"), class = 
	"factor"), chngex75 = c(3.44697, -2.84312, -0.63888, 0.91474, 
	27.52827, 18.58261, 15.79292, 1.44333, -1.02077, 0.49458, 22.83059,
	12.89455, 0.25738, 1.59568, -2.80343, 37.65431, 10.65676, 2.41913, 
	4.91362, 9.9384599999999984, 0.04492, 1.93853, 54.13197, 4.04763, 
	-4.78494
	, 2.53347, 36.10757, 4.73297, -2.18995, 4.6672, 1.2020900000000002,
	0, 8.06798, -1.79143, 8.34927, 3.82773, 11.62342, 2.3633, -4.13043,
	1.51669, 34.643880000000004, 1.46547, 41.69817, 15.95272), 
	chngex85 = c(-2.22615, -11.9725, -11.4966, -3.14511, 12.77215, 
	25.22128, 11.92314, -5.8118, 0.9235, -10.7561, 48.02549, 27.0518, 
	-9.66089
	, -10.0165, -12, 35.84377, 2.75455, 4.6399800000000008, 6.94463, 
	10.12818, -5.8101900000000008, -8.94559, 10.73435, -9.32146, 
	-9.98505, -4.12822, 47.86589, -3.99072, -12.0211, -3.7647, 
	-6.34609, 0, 5.34709, -3.87604, 2.98435, -10.2346, 7.77219, 
	-7.48164, -11.4051, -1.19359, 32.1791, -6.49466, 48.92574, 
	36.66251), chngin75 = c(3.62836, -2.14455, -2.1776399999999996, 
	0.95945, 27.02101, 17.09647, 14.48453, 0.08685, -2.40715, 1.23206, 
	18.14339, 9.01533, 1.34951, 1.55156, -1.89497, 37.65242, 11.08797, 
	1.82156, 2.44539, 8.20899, 11.1806, 2.8799800000000004, 54.21602, 
	5.41199, -3.43752, 2.9604, 35.51927, 3.39187, -1.4449, 6.68496, 
	1.78928, -1.2653, 9.07668, -2.59469, 8.35791, 5.0951000000000008, 
	7.67709, 3.01878, -3.19965, 0.58023, 32.24987, 3.4174000000000004, 
	41.48201, 13.52651), chngin85 = c(3.99243, -3.0003700000000004, 
	-4.454, -0.37619, 12.64657, 20.69606, 10.13828, -1.39634, -1.64527,
	-1.8000100000000002, 38.08751, 15.95062, -0.85196, 
	-1.0754300000000002, -2.19218, 31.21122, 9.90171, 6.46403, 4.77629,
	6.08801, 18.13681, -1.37732, 17.694849999999998, 1.35831, -4.3655, 
	-0.95035
	, 49.22527, 1.78159, -2.19218, 3.55156, 2.07169, -4.6994, 5.50364, 
	-3.73536
	, 11.4217, -0.19617, 8.5365300000000016, 1.08788, -2.01475, 
	1.84642, 37.06542, 2.23105, 52.36151, 30.20931)), class = 
	"data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8",
	"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
	"20", "21", "22", "23", "24", "25", "26", "27", "28", "29", "30", 
	"31", "32", "33", "34", "35", "36", "37", "38", "39", "40", "41", 
	"42", "43", "44"))
"prdq"<-
structure(.Data = list(quality = c(29, 38, 39, 38, 42, 48, 50, 55, 56, 57, 
	56, 61, 68, 67, 69, 69, 70, 68, 69, 79, 89, 84, 87, 98, 100, 140, 
	170), productiv = c(31, 26, 27, 23, 15, 20, 17, 12, 16, 18, 25, 20,
	21, 26, 30, 32, 31, 37, 54, 18, 17, 28, 44, 23, 25, 21, 28), japan
	 = c(0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 1,
	0, 0, 0, 0, 0, 0), qualnonj = c(29, 38, 68, 67, 69, 69, 70, 68, 69,
	79, 84, 87, 98, 100, 140, 170, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
	NA, NA), qualjapn = c(39, 38, 42, 48, 50, 55, 56, 57, 56, 61, 89, 
	NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), 
	prodnonj = c(31, 26, 21, 26, 30, 32, 31, 37, 54, 18, 28, 44, 23, 
	25, 21, 28, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA), prodjapn
	 = c(27, 23, 15, 20, 17, 12, 16, 18, 25, 20, 17, NA, NA, NA, NA, 
	NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)), class = 
	"data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8",
	"9", "10", "11", "12", "13", "14", "15", "16", "17", "18", "19", 
	"20", "21", "22", "23", "24", "25", "26", "27"))
"rtn"<-
structure(.Data = list(year = c(1976, 1977, 1978, 1979, 1980, 1981, 1982, 
	1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993), 
	sandp = c(10000, 9281.2618, 9885.7197, 11710.427, 15509.067, 
	14752.55, 17924.064999999998, 21949.377, 23315.074, 30692.293, 
	36407.253, 38292.406, 44609.936, 58702.304, 56870.986, 74159.426, 
	79803.551, 87831.507), vanguard = c(10000, 9215.649, 9756.9082, 
	11517.425, 15193.239, 14402.241, 17422.847000000002, 21132.846, 
	22446.111, 29454.943, 34774.475, 36410.597, 42316.969, 55589.213, 
	53741.335, 69982.907999999992, 75178.046, 82613.237)), class = 
	"data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", "8",
	"9", "10", "11", "12", "13", "14", "15", "16", "17", "18"))
"rock"<-
structure(.Data = list(title = structure(.Data = c(1, 2, 3, 4, 5, 6, 7, 8, 
	9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 
	26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42,
	43, 44), .Label = c("100% Pure Love", "Action", "All I Wanna Do", 
	"Always", "Always In My Heart", "Another Night", 
	"Any Time; Any Place", "Anytime You Need A Friend", 
	"At Your Best (You Are Love)", "Back & Forth", "Body & Soul", 
	"Bop Gun (One Nation)", "Can You Feel The Love Tonight", 
	"Circle of Life", "Closer", "Crazy", "Do You Wanna Get Funky", 
	"Don't Turn Around", "Fantastic Voyage", "Far Behind", 
	"Flava In Ya Ear", "Funkdafied", "I Miss You", "I Swear", 
	"I'd Give Anything", "I'll Make Love To You", "If You Go", 
	"Letitgo", "Love Is All Around", "Lucky One", "Nappy Heads", 
	"Never Lie", "Nuttin' But Love", "Romatic Call", "Shine", 
	"Stay (I Missed You)", "Stroke You Up", "Summer Bunnies", 
	"The Way She Loves Me", "This D.J.", "When Can I See You", 
	"Wild Night", "You Mean The World To Me", "Your Body's Callin'"), 
	class = "factor"), sales = c(26, 43, 40, 65, 32, 69, 33, 61, 13, 
	29, 27, 16, 14, 34, 35, 45, 23, 25, 4, 53, 12, 6, 18, 8, 19, 1, 51,
	52, 58, 60, 37, 10, 28, 36, 21, 3, 2, 41, 38, 5, 11, 7, 63, 47), 
	saleslst = c(31, 42, 61, 57, 29, 76, 28, 52, 76, 22, 44, 21, 12, 
	48, 41, 37, 30, 20, 2, 50, 16, 5, 13, 6, 18, 1, 49, 53, 67, 66, 39,
	11, 32, 43, 17, 3, 4, 47, 36, 7, 10, 8, 54, 33), saleswk = c(16, 4,
	2, 19, 10, 1, 15, 14, 1, 20, 2, 7, 15, 2, 14, 15, 6, 17, 15, 2, 5, 
	15, 18, 18, 4, 4, 17, 3, 3, 3, 9, 6, 9, 4, 16, 15, 7, 3, 6, 7, 11, 
	12, 23, 16), play = c(18, 43, 7, 33, 42, 35, 21, 15, 38, 17, 65, 
	41, 4, 49, 58, 29, 52, 5, 13, 34, 61, 26, 25, 12, 63, 1, 8, 40, 46,
	22, 74, 54, 45, 66, 9, 2, 16, 68, 24, 20, 6, 3, 14, 44), playlst
	 = c(17, 45, 15, 31, 34, 42, 13, 12, 37, 18, 68, 49, 3, 76, 71, 22,
	52, 5, 11, 35, 76, 21, 27, 9, 53, 2, 6, 43, 46, 30, 74, 60, 47, 73,
	8, 1, 23, 62, 20, 25, 7, 4, 10, 40), playwk = c(14, 8, 5, 20, 14, 
	3, 17, 17, 5, 19, 2, 5, 17, 1, 2, 14, 7, 21, 13, 9, 1, 14, 15, 21, 
	6, 5, 19, 4, 8, 5, 5, 3, 6, 2, 18, 20, 7, 3, 10, 11, 13, 16, 23, 
	27), xplay = c(-1, 2, 8, -2, -8, 7, -8, -3, -1, 1, 3, 8, -1, 27, 
	13, -7, 0, 0, -2, 1, 15, -5, 2, -3, -10, 1, -2, 3, 0, 8, 0, 6, 2, 
	7, -1, -1, 7, -6, -4, 5, 1, 1, -4, -4), xsales = c(5, -1, 21, -8, 
	-3
	, 7, -5, -9, 63, -7, 17, 5, -2, 14, 6, -8, 7, -5, -2, -3, 4, -1, 
	-5, -2, -1, 0, -2, 1, 9, 6, 2, 1, 4, 7, -4, 0, 2, 6, -2, 2, -1, 1, 
	-9
	, -14)), class = "data.frame", row.names = c("1", "2", "3", "4", 
	"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", 
	"17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", 
	"28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", 
	"39", "40", "41", "42", "43", "44"))
"sex"<-
structure(.Data = list(male = c(1, 3, 6, 6, 47, 1, 175, 0, 10, 2, 50, 2, 1,
	1, 1, 1, 5, 1, 5, 4, 1, 2, 3, 3, 20, 1, 10, 10, 10, 4, 1, 0, 10, 2,
	3, 6, 0, 2, 12, 4, 12, 10, 0, 20, 3, 0, 10, 10, 2, 1, 4, 40, 2, 12,
	5, 3, 5, 15, 2, 30, 13, 18, 30, 5, 2, 4, 5, 1, 2, 20, 4, 5, 10, 
	150, 10, 0, 101, 8, 7, 4, 100, 6, 6, 3, 6, 1, 1, 10, 1, 15, 1, 1, 
	1, 10, 1, 30, 1, 4, 4, 3, 1, 7, 4, 4, 1, 2, 5, 1, 5, 6, 0, 3, 2, 2,
	1, 2, 2, 1, 30, 6, 5, 15, 28, 3, 1, 4, 10, 5, 20, 8, 5, 0, 1, 2, 
	10, 3, 8, 6, 12, 30, 0, 4, 5, 15, 1, 0, 10, 3, 4, 100, 1, 1, 30, 
	15, 0, 0, 4, 5, 50, 1, 20, 2, 50, 0, 20, 1, 3, 0, 6, 0, 50, 0, 2, 
	1, 20, 20, 4, 3, 0, 0, 2, 40, 1, 10, 2, 4, 1, 1, 4, 45, 40, 2, 50, 
	15, 25, 0, 4, 0, 6, 0, 20, 9, 2, 200, 12, 20, 1, 1, 40, 6, 2, 40, 
	1, 125, 0, 6, 0, 2, 8, 4, 7, 1, 3, 4, 0, 5, 6, 2, 1, 0, 3, 2, 12, 
	8, 3, 2, 2, 5, 1, 0, 10, 5, 1, 4, 20, 2, 1, 0, 3, 0, 2, 20, 30, 4, 
	4, 2, 150, 0, 40, 1, 101, 1, 0, 0, 6, 6, 10, 2, 0, 0, 6, 4, 3, 1, 
	4, 0, 1, 10, 30, 2, 10, 6, 4, 0, 1, 50, 1, 9, 4, 50, 0, 8, 2, 5, 2,
	15, 4, 50, 5, 1, 2, 2, 3, 2, 4, 15, 10, 30, 10, 1, 15, 1, 2, 3, 1, 
	3, 1, 5, 2, 6, 50, 3, 2, 3, 2, 6, 5, 4, 7, 0, 3, 0, 2, 20, 1, 9, 
	10, 1, 1, 3, 1, 1, 2, 1, 0, 20, 75, 5, 10, 1, 2, 2, 1, 2, 4, 1, 90,
	4, 5, 12, 12, 6, 30, 20, 5, 15, 10, 2, 5, 5, 5, 1, 12, 24, 1, 50, 
	8, 30, 15, 20, 15, 4, 0, 4, 1, 6, 1, 2, 4, 30, 50, 1, 200, 10, 1, 
	0, 5, 6, 2, 1, 4, 2, 6, 3, 5, 1, 20, 0, 6, 4, 8, 4, 10, 1, 1, 0, 3,
	20, 4, 0, 0, 3, 20, 11, 1, 0, 20, 1, 1, 1, 20, 4, 3, 100, 20, 2, 0,
	0, 1, 6, 0, 1, 1, 2, 15, 25, 3, 4, 2, 0, 1, 3, 2, 1, 1, 7, 1, 15, 
	0, 6, 1, 1, 4, 1, 200, 12, 1, 30, 12, 2, 20, 3, 1, 2, 3, 0, 20, 1, 
	8, 20, 24, 0, 18, 18, 4, 253, 7, 5, 2, 5, 27, 20, 20, 10, 1, 35, 
	11, 20, 0, 10, 5, 5, 0, 8, 20, 0, 10, 40, 1, 20, 40, 20, 1, 2, 1, 
	1, 3, 2, 2, 35, 100, 22, 40, 6, 1, 2, 20, 30, 4, 1, 25, 10, 3, 30, 
	3, 3, 6, 4, 20, 0, 0, 1, 5, 20, 1, 1, 2, 1, 1, 1, 2, 3, 1, 10, 1, 
	0, 1, 3, 8, 6, 10, 8, 1, 1, 20, 2, 0, 1, 100, 6, 1, 20, 2, 1, 0, 1,
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	50, 15, 20, 4, 0, 20, 12, 1, 4, 10, 5, 0, 20, 1, 35, 4, 4, 5, 1, 7,
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	1, 12, 0, 13, 1, 3, 10, 5, 4, 2, 4, 3, 1, 20, 0, 1, 1, 25, 3, 0, 7,
	19, 2, 1, 10, 12, 20, 3, 1, 5, 4, 0, 0, 4, 10, 20, 2, 0, 30, 4, 10,
	2, 4, 25, 1, 15, 100, 20, 1, 1, 2, 6, 1, 6, 10, 15, 1, 2, 24, 0, 
	25, 25, 50, 0, 12, 33, 10, 4, 18, 4, 40, 1, 8, 20, 1, 130, 0, 1, 4,
	1, 7, 4, 1, 15, 14, 1, 1, 0, 40, 1, 5, 10, 20, 0, 1, 2, 22, 0, 2, 
	3, 24, 2, 0, 40, 3, 2, 3, 6, 6, 0, 3, 5, 2, 8, 1, 4, 8, 0, 1, 3, 
	100, 4, 4, 3, 10, 10, 12, 2, 2, 4, 20, 0, 3, 1, 35, 5, 1, 0, 1, 8, 
	4, 1, 100, 40, 1, 4, 75, 6, 100, 4, 1, 25, 100, 20, 8, 5, 9, 5, 20,
	10, 4, 175, 1, 1, 10, 6, 4, 5, 4, 12, 4, 1, 5, 12, 1, 5, 8, 130, 1,
	5, 3, 1, 10, 1, 6, 1, 3, 50, 1, 5, 6, 3, 5, 3, 15, 7, 0, 15, 1, 4, 
	20, 2, 10, 7, 20, 40, 10, 4, 6, 40, 3, 20, 10, 0, 1, 5, 10, 0, 12, 
	0, 1, 8, 5, 8, 0, 0, 5, 3, 4, 0, 2, 20, 1, 1, 12, 1, 5, 7, 5, 10, 
	15, 3, 20, 1, 4, 0, 1, 2, 3, 1, 100, 1, 20, 50, 1, 6, 2, 0, 2, 2, 
	14, 0, 30, 0, 20, 1, 10, 2, 3, 35, 2, 1, 10, 3, 10, 1, 5, 1, 10, 0,
	2, 1, 40, 0, 5, 4, 0, 4, 7, 50, 10, 3, 6, 3, 1, 6, 5, 1, 100, 3, 
	40, 15, 1, 2, 5, 10, 50, 3, 1, 1, 1, 2, 5, 1, 3, 1, 5, 20, 1, 200, 
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	20, 17, 1, 2, 1, 6, 6, 28, 15, 4, 3, 6, 4, 68, 4, 3, 1, 3, 0, 2, 1,
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	8, 4, 0, 10, 1, 3, 0, 40, 20, 5, 5, 100, 4, 4, 3, 6, 6, 4, 2, 6, 1,
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	20, 3, 75, 10, 6, 1, 5, 3, 0, 4, 3, 5, 10, 75, 10, 4, 0, 0, 5, 25, 
	30, 4, 8, 3, 3, 12, 18, 10, 3, 6, 0, 20, 2, 1, 6, 20, 6, 1, 3, 2, 
	1, 30, 50, 8, 1, 0, 100, 20, 10, 3, 1, 15, 2, 6, 3, 50, 50, 2, 2, 
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	2, 1, 2, 15, 0, 1, 4, 9, 1, 5, 1, 6, 6, 30, 2, 2, 6, 1, 2, 20, 12, 
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	0, 20, 6, 5, 2, 10, 0, 2, 3, 4, 1, 1, 1, 1, 5, 100, 1, 0, 1, 1, 1, 
	12, 1, 1, 15, 0, 2, 1, 1, 4, 15, 1, 2, 1, 1, 4, 1, 1, 1, 1, 0, 2, 
	1, 1, 0, 1, 1, 1, 2, 1, 1, 12, 2, 2, 1, 6, 7, 1, 3, 0, 5, 15, 6, 
	45, 2, 1, 2, 2, 10, 1, 3, 2, 5, 1, 1, 4, 2, 2, 0, 1, 7, 6, 30, 2, 
	1, 0, 1, 0, 0, 1, 0, 3, 20, 1, 1, 1, 1, 3, 1, 0, 1, 1, 1, 0, 6, 1, 
	3, 5, 0, 20, 1, 3, 1, 1, 15, 1, 12, 1, 0, 5, 1, 1, 1, 2, 5, 2, 10, 
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	1, 1, 5, 0, 4, 1, 2, 3, 8, 1, 1, 3, 1, 1, 1, 2, 1, 4, 20, 1, 1, 1, 
	30, 0, 3, 6, 5, 2, 3, 3, 1, 20, 3, 1, 2, 1, 15, 1, 1, 8, 1, 1, 1, 
	2, 1, 4, 1, 4, 10, 3, 4, 0, 1, 1, 4, 1, 2, 2, 1, 1, 1, 2, 45, 0, 0,
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	10, 0, 1, 1, 1, 1, 1, 2, 2, 1, 8, 4, 2, 1, 4, 1, 1, 20, 0, 1, 0, 1,
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	7, 0, 3, 1, 4, 0, 1, 10, 16, 4, 1, 1, 0, 1, 1, 2, 1, 8, 8, 0, 2, 3,
	2, 1, 1, 8, 1, 2, 2, 1, 1, 1, 2, 1, 7, 1, 2, 35, 5, 50, 2, 0, 4, 1,
	2, 2, 6, 3, 0, 1, 2, 1, 0, 8, 1, 3, 2, 0, 0, 5, 1, 7, 1, 6, 1, 1, 
	1, 0, 1, 2, 5, 1, 2, 2, 3, 10, 1, 1, 1, 2, 10, 0, 1, 1, 3, 1, 1, 3,
	2, 1, 1, 5, 1, 4, 1, 0, 0, 3, 4, 3, 0, 1, 5, 1, 6, 1, 0, 5, 7, 1, 
	4, 1, 1, 5, 1, 1, 1, 1, 0, 2, 3, 8, 3, 2, 4, 10, 20, 1, 1, 3, 1, 1,
	1, 1, 1, 1, 0, 20, 2, 1, 0, 1, 1, 10, 0, 1, 4, 4, 1, 2, 1, 2, 3, 
	55, 0, 1, 1, 3, 3, 1, 3, 1, 1, 1, 1, 6, 2, 1, 1, 8, 4, 0, 1, 1, 2, 
	1, 6, 2, 1, 3, 0, 1, 1, 5, 1, 0, 7, 1, 1, 1, 1, 4, 1, 45, 1, 1, 3, 
	2, 15, 10, 1, 1, 1, 1, 2, 2, 3, 1, 2, 1, 2, 1, 0, 1, 1, 2, 1, 1, 2,
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	2, 1, 1, 3, 2, 1, 6, 2, 4, 3, 2, 4, 1, 3, 1, 1, 1, 1, 1, 3, 3, 2, 
	30, 1, 1, 1, 1, 1, 1, 1, 1, 3, 0, 4, 35, 1, 7, 1, 1, 3, 5, 5, 5, 
	25, 12, 1, 0, 6, 3, 1, 6, 1, 1, 0, 1, 1, 0, 3, 1, 2, 4, 1, 1, 3, 3,
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	20, 1, 7, 3, 0, 1, 2, 1, 1, 5, 1, 25, 2, 1, 0, 4, 3, 10, 5, 1, 1, 
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	5, 3, 0, 1, 1, 3, 6, 1, 2, 3, 3, 1, 1, 1, 4, 1, 10, 2, 5, 1, 2, 2, 
	2, 3, 2, 1, 2, 3, 1, 2, 1, 1, 8, 1, 0, 1, 0, 3, 1, 1, 7, 1, 2, 35, 
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	"416", "417", "418", "419", "420", "421", "422", "423", "424", 
	"425", "426", "427", "428", "429", "430", "431", "432", "433", 
	"434", "435", "436", "437", "438", "439", "440", "441", "442", 
	"443", "444", "445", "446", "447", "448", "449", "450", "451", 
	"452", "453", "454", "455", "456", "457", "458", "459", "460", 
	"461", "462", "463", "464", "465", "466", "467", "468", "469", 
	"470", "471", "472", "473", "474", "475", "476", "477", "478", 
	"479", "480", "481", "482", "483", "484", "485", "486", "487", 
	"488", "489", "490", "491", "492", "493", "494", "495", "496", 
	"497", "498", "499", "500", "501", "502", "503", "504", "505", 
	"506", "507", "508", "509", "510", "511", "512", "513", "514", 
	"515", "516", "517", "518", "519", "520", "521", "522", "523", 
	"524", "525", "526", "527", "528", "529", "530", "531", "532", 
	"533", "534", "535", "536", "537", "538", "539", "540", "541", 
	"542", "543", "544", "545", "546", "547", "548", "549", "550", 
	"551", "552", "553", "554", "555", "556", "557", "558", "559", 
	"560", "561", "562", "563", "564", "565", "566", "567", "568", 
	"569", "570", "571", "572", "573", "574", "575", "576", "577", 
	"578", "579", "580", "581", "582", "583", "584", "585", "586", 
	"587", "588", "589", "590", "591", "592", "593", "594", "595", 
	"596", "597", "598", "599", "600", "601", "602", "603", "604", 
	"605", "606", "607", "608", "609", "610", "611", "612", "613", 
	"614", "615", "616", "617", "618", "619", "620", "621", "622", 
	"623", "624", "625", "626", "627", "628", "629", "630", "631", 
	"632", "633", "634", "635", "636", "637", "638", "639", "640", 
	"641", "642", "643", "644", "645", "646", "647", "648", "649", 
	"650", "651", "652", "653", "654", "655", "656", "657", "658", 
	"659", "660", "661", "662", "663", "664", "665", "666", "667", 
	"668", "669", "670", "671", "672", "673", "674", "675", "676", 
	"677", "678", "679", "680", "681", "682", "683", "684", "685", 
	"686", "687", "688", "689", "690", "691", "692", "693", "694", 
	"695", "696", "697", "698", "699", "700", "701", "702", "703", 
	"704", "705", "706", "707", "708", "709", "710", "711", "712", 
	"713", "714", "715", "716", "717", "718", "719", "720", "721", 
	"722", "723", "724", "725", "726", "727", "728", "729", "730", 
	"731", "732", "733", "734", "735", "736", "737", "738", "739", 
	"740", "741", "742", "743", "744", "745", "746", "747", "748", 
	"749", "750", "751", "752", "753", "754", "755", "756", "757", 
	"758", "759", "760", "761", "762", "763", "764", "765", "766", 
	"767", "768", "769", "770", "771", "772", "773", "774", "775", 
	"776", "777", "778", "779", "780", "781", "782", "783", "784", 
	"785", "786", "787", "788", "789", "790", "791", "792", "793", 
	"794", "795", "796", "797", "798", "799", "800", "801", "802", 
	"803", "804", "805", "806", "807", "808", "809", "810", "811", 
	"812", "813", "814", "815", "816", "817", "818", "819", "820", 
	"821", "822", "823", "824", "825", "826", "827", "828", "829", 
	"830", "831", "832", "833", "834", "835", "836", "837", "838", 
	"839", "840", "841", "842", "843", "844", "845", "846", "847", 
	"848", "849", "850", "851", "852", "853", "854", "855", "856", 
	"857", "858", "859", "860", "861", "862", "863", "864", "865", 
	"866", "867", "868", "869", "870", "871", "872", "873", "874", 
	"875", "876", "877", "878", "879", "880", "881", "882", "883", 
	"884", "885", "886", "887", "888", "889", "890", "891", "892", 
	"893", "894", "895", "896", "897", "898", "899", "900", "901", 
	"902", "903", "904", "905", "906", "907", "908", "909", "910", 
	"911", "912", "913", "914", "915", "916", "917", "918", "919", 
	"920", "921", "922", "923", "924", "925", "926", "927", "928", 
	"929", "930", "931", "932", "933", "934", "935", "936", "937", 
	"938", "939", "940", "941", "942", "943", "944", "945", "946", 
	"947", "948", "949", "950", "951", "952", "953", "954", "955", 
	"956", "957", "958", "959", "960", "961", "962", "963", "964", 
	"965", "966", "967", "968", "969", "970", "971", "972", "973", 
	"974", "975", "976", "977", "978", "979", "980", "981", "982", 
	"983", "984", "985", "986", "987", "988", "989", "990", "991", 
	"992", "993", "994", "995", "996", "997", "998", "999", "1000", 
	"1001", "1002", "1003", "1004", "1005", "1006", "1007", "1008", 
	"1009", "1010", "1011", "1012", "1013", "1014", "1015", "1016", 
	"1017", "1018", "1019", "1020", "1021", "1022", "1023", "1024", 
	"1025", "1026", "1027", "1028", "1029", "1030", "1031", "1032", 
	"1033", "1034", "1035", "1036", "1037", "1038", "1039", "1040", 
	"1041", "1042", "1043", "1044", "1045", "1046", "1047", "1048", 
	"1049", "1050", "1051", "1052", "1053", "1054", "1055", "1056", 
	"1057", "1058", "1059", "1060", "1061", "1062", "1063", "1064", 
	"1065", "1066", "1067", "1068", "1069", "1070", "1071", "1072", 
	"1073", "1074", "1075", "1076", "1077", "1078", "1079", "1080", 
	"1081", "1082", "1083", "1084", "1085", "1086", "1087", "1088", 
	"1089", "1090", "1091", "1092", "1093", "1094", "1095", "1096", 
	"1097", "1098", "1099", "1100", "1101", "1102", "1103", "1104", 
	"1105", "1106", "1107", "1108", "1109", "1110", "1111", "1112", 
	"1113", "1114", "1115", "1116", "1117", "1118", "1119", "1120", 
	"1121", "1122", "1123", "1124", "1125", "1126", "1127", "1128", 
	"1129", "1130", "1131", "1132", "1133", "1134", "1135", "1136", 
	"1137", "1138", "1139", "1140", "1141", "1142", "1143", "1144", 
	"1145", "1146", "1147", "1148", "1149", "1150", "1151", "1152", 
	"1153", "1154", "1155", "1156", "1157", "1158", "1159", "1160", 
	"1161", "1162", "1163", "1164", "1165", "1166", "1167", "1168", 
	"1169", "1170", "1171", "1172", "1173", "1174", "1175", "1176", 
	"1177", "1178", "1179", "1180", "1181", "1182", "1183", "1184", 
	"1185", "1186", "1187", "1188", "1189", "1190", "1191", "1192", 
	"1193", "1194", "1195", "1196", "1197", "1198", "1199", "1200", 
	"1201", "1202", "1203", "1204", "1205", "1206", "1207", "1208", 
	"1209", "1210", "1211", "1212", "1213", "1214", "1215", "1216", 
	"1217", "1218", "1219", "1220", "1221", "1222", "1223", "1224", 
	"1225", "1226", "1227", "1228", "1229", "1230", "1231", "1232", 
	"1233", "1234", "1235", "1236", "1237", "1238", "1239", "1240", 
	"1241", "1242", "1243", "1244", "1245", "1246", "1247", "1248", 
	"1249", "1250", "1251", "1252", "1253", "1254", "1255", "1256", 
	"1257", "1258", "1259", "1260", "1261", "1262", "1263", "1264", 
	"1265", "1266", "1267", "1268", "1269", "1270", "1271", "1272", 
	"1273", "1274", "1275", "1276", "1277", "1278", "1279", "1280", 
	"1281", "1282", "1283", "1284", "1285", "1286", "1287", "1288", 
	"1289", "1290", "1291", "1292", "1293", "1294", "1295", "1296", 
	"1297", "1298", "1299", "1300", "1301", "1302", "1303", "1304", 
	"1305", "1306", "1307", "1308", "1309", "1310", "1311", "1312", 
	"1313", "1314", "1315", "1316", "1317", "1318", "1319", "1320", 
	"1321", "1322", "1323", "1324", "1325", "1326", "1327", "1328", 
	"1329", "1330", "1331", "1332", "1333", "1334", "1335", "1336", 
	"1337", "1338", "1339", "1340", "1341", "1342", "1343", "1344", 
	"1345", "1346", "1347", "1348", "1349", "1350", "1351", "1352", 
	"1353", "1354", "1355", "1356", "1357", "1358", "1359", "1360", 
	"1361", "1362", "1363", "1364", "1365", "1366", "1367", "1368", 
	"1369", "1370", "1371", "1372", "1373", "1374", "1375", "1376", 
	"1377", "1378", "1379", "1380", "1381", "1382", "1383", "1384", 
	"1385", "1386", "1387", "1388", "1389", "1390", "1391", "1392", 
	"1393", "1394", "1395", "1396", "1397", "1398", "1399", "1400", 
	"1401", "1402", "1403", "1404", "1405", "1406", "1407", "1408", 
	"1409", "1410", "1411", "1412", "1413", "1414", "1415", "1416", 
	"1417", "1418", "1419", "1420", "1421", "1422", "1423", "1424", 
	"1425", "1426", "1427", "1428", "1429", "1430", "1431", "1432", 
	"1433", "1434", "1435", "1436", "1437", "1438", "1439", "1440", 
	"1441", "1442", "1443", "1444", "1445", "1446", "1447", "1448", 
	"1449", "1450", "1451", "1452", "1453", "1454", "1455", "1456", 
	"1457", "1458", "1459", "1460", "1461", "1462", "1463", "1464", 
	"1465", "1466", "1467", "1468", "1469", "1470", "1471", "1472", 
	"1473", "1474", "1475", "1476", "1477", "1478", "1479", "1480", 
	"1481", "1482", "1483", "1484", "1485", "1486", "1487", "1488", 
	"1489", "1490", "1491", "1492", "1493", "1494", "1495", "1496", 
	"1497", "1498", "1499", "1500", "1501", "1502", "1503", "1504", 
	"1505", "1506", "1507", "1508", "1509", "1510", "1511", "1512", 
	"1513", "1514", "1515", "1516", "1517", "1518", "1519", "1520", 
	"1521", "1522", "1523", "1524", "1525", "1526", "1527", "1528", 
	"1529", "1530", "1531", "1532", "1533", "1534", "1535", "1536", 
	"1537", "1538", "1539", "1540", "1541", "1542", "1543", "1544", 
	"1545", "1546", "1547", "1548", "1549", "1550", "1551", "1552", 
	"1553", "1554", "1555", "1556", "1557", "1558", "1559", "1560", 
	"1561", "1562", "1563", "1564", "1565", "1566", "1567", "1568", 
	"1569", "1570", "1571", "1572", "1573", "1574", "1575", "1576", 
	"1577", "1578", "1579", "1580", "1581", "1582", "1583", "1584", 
	"1585", "1586", "1587", "1588", "1589", "1590", "1591", "1592", 
	"1593", "1594", "1595", "1596", "1597", "1598", "1599", "1600", 
	"1601", "1602", "1603", "1604", "1605", "1606", "1607", "1608", 
	"1609", "1610", "1611", "1612", "1613", "1614", "1615", "1616", 
	"1617", "1618", "1619", "1620", "1621", "1622", "1623", "1624", 
	"1625", "1626", "1627", "1628", "1629", "1630", "1631", "1632", 
	"1633", "1634", "1635", "1636", "1637", "1638", "1639", "1640", 
	"1641", "1642", "1643", "1644", "1645", "1646", "1647", "1648", 
	"1649", "1650", "1651", "1652", "1653", "1654", "1655", "1656", 
	"1657", "1658", "1659", "1660", "1661", "1662", "1663", "1664", 
	"1665", "1666", "1667", "1668", "1669", "1670", "1671", "1672", 
	"1673", "1674", "1675", "1676", "1677", "1678", "1679", "1680", 
	"1681", "1682", "1683", "1684", "1685", "1686", "1687", "1688", 
	"1689", "1690", "1691", "1692", "1693", "1694", "1695", "1696", 
	"1697", "1698", "1699", "1700", "1701", "1702", "1703", "1704", 
	"1705", "1706", "1707", "1708", "1709", "1710", "1711", "1712", 
	"1713", "1714", "1715", "1716", "1717", "1718", "1719", "1720", 
	"1721", "1722", "1723", "1724", "1725", "1726", "1727", "1728", 
	"1729", "1730", "1731", "1732", "1733", "1734", "1735", "1736", 
	"1737", "1738", "1739", "1740", "1741", "1742", "1743", "1744", 
	"1745", "1746", "1747", "1748", "1749", "1750", "1751", "1752", 
	"1753", "1754", "1755", "1756", "1757", "1758", "1759", "1760", 
	"1761", "1762", "1763", "1764", "1765", "1766", "1767", "1768", 
	"1769", "1770", "1771", "1772", "1773", "1774", "1775", "1776", 
	"1777", "1778", "1779", "1780", "1781", "1782", "1783", "1784", 
	"1785", "1786", "1787", "1788", "1789", "1790", "1791", "1792", 
	"1793", "1794", "1795", "1796", "1797", "1798", "1799", "1800", 
	"1801", "1802", "1803", "1804", "1805", "1806", "1807", "1808", 
	"1809", "1810", "1811", "1812", "1813", "1814", "1815", "1816", 
	"1817", "1818", "1819", "1820", "1821", "1822", "1823", "1824", 
	"1825", "1826", "1827", "1828", "1829", "1830", "1831", "1832", 
	"1833", "1834", "1835", "1836", "1837", "1838", "1839", "1840", 
	"1841", "1842", "1843", "1844", "1845", "1846", "1847", "1848", 
	"1849", "1850"))
"subway"<-
structure(.Data = list(usage = c(1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 1, 1, 1, 
	1, 1, 1, 1, 0, 1, 1, 0, 1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 1, 1, 0, 1, 
	1, 1, 1, 1, 0, 1, 1, 1, 0, 1, 0, 0, 0, 0, 1, 1, 1, 1, 0, 1, 1, 1, 
	1, 1, 0, 1), clnstat = c(1, 2, 2, 2, 1, 1, 2, 1, 2, 1, 4, 2, 1, 2, 
	2, 1, 1, 1, 1, 3, 2, 1, 4, 2, 4, 1, 1, 2, 4, 2, 2, 2, 1, 2, 4, 1, 
	2, 3, 5, NA, 2, 2, 3, 2, 1, 1, 2, 1, 1, 2, 2, 1, 2, 4, 1, 1, 2, 2, 
	4, 1, 2, 2), clntrain = c(3, 2, 5, 4, 1, 1, 3, 4, 3, 1, 4, 3, 1, 3,
	2, 1, 2, 1, 1, 3, 3, 2, 4, 3, 4, 2, 2, 2, 3, 4, 2, 4, 1, 2, 4, 1, 
	2, 3, 5, 5, 3, 4, 3, 2, 2, 2, 2, 1, 1, 2, 3, 1, 1, 4, 1, 1, 2, 2, 
	4, 1, 2, 3), safstat = c(3, 3, 4, 5, 1, 1, 2, 2, 3, 1, 3, 3, 2, 2, 
	3, 1, 2, 1, 3, 3, 5, 1, 4, 1, 4, 2, 2, 2, 4, 4, 2, 2, 2, 3, 4, 1, 
	1, 4, 3, 4, 4, 3, 3, 3, 1, 1, 3, 1, 1, 4, 3, NA, 1, 2, 1, 1, 2, 2, 
	3, 1, 2, 3), saftrain = c(3, 3, 2, 5, 1, 1, 3, 1, 3, 1, 2, 5, 1, 2,
	3, 1, 3, 1, 3, 3, 5, 1, 3, 1, 3, 2, 2, 2, 4, 3, 3, 3, 2, 3, 4, 1, 
	1, 4, 3, 4, 4, 3, 3, 3, 1, 1, 2, 1, 1, 3, 3, NA, 1, 2, 1, 1, 2, 2, 
	3, 1, 2, 3), crwdstat = c(1, 3, 2, 4, 1, 2, 2, 2, 3, 4, 3, 4, 3, 4,
	2, 1, 2, 1, 1, 1, 3, 3, 3, 3, 3, 2, 1, 3, 3, 3, 2, 4, 1, 4, 3, 3, 
	2, 2, 5, NA, 3, 4, 2, 3, 1, 3, 3, 1, NA, 3, 3, 2, 2, 4, 1, 4, 2, 2,
	3, 2, 2, 3), crwdtran = c(1, 2, 1, 3, 1, 1, 1, 4, 2, 4, 3, 2, 1, 3,
	1, 1, 2, 1, 1, 1, 5, 3, 3, 3, 1, 1, 1, 2, 1, 1, 2, 1, 1, 4, 3, 3, 
	2, 1, 5, NA, 4, 2, 2, 3, 2, 2, 3, 1, NA, 3, 3, NA, 1, 3, 1, 4, 2, 
	1, 4, 1, 2, 2), infostat = c(2, 1, 5, 2, 3, 2, 2, 2, 2, 3, 3, 2, 2,
	1, 2, 4, 1, 3, 1, 2, 5, 3, 4, 1, 1, 2, 1, 3, 1, 3, 3, 5, 3, 2, 4, 
	2, 2, 3, 4, 2, 4, 2, 5, 4, 1, 2, 1, 2, 1, 2, 4, NA, 1, 4, 1, 5, 1, 
	3, 2, 1, 3, 4), infotran = c(2, 1, 3, 2, 3, 5, 2, 2, 2, 1, 3, 2, 3,
	1, 3, 2, 1, 1, 1, 1, 1, 3, 4, 1, 4, 2, 3, 4, 3, 3, 3, 5, 2, NA, 2, 
	2, 2, 2, 3, 1, 4, 3, 2, 4, 3, 2, 1, 1, 1, 1, 4, NA, 1, 3, 1, 2, 1, 
	2, 2, 1, 2, 1), convstop = c(3, 4, 5, 5, 2, 5, 3, 5, 3, 1, 3, 4, 3,
	5, 4, 2, 5, 4, 5, 4, 5, 5, 5, 2, 5, 3, 5, 4, 5, 3, 3, 5, 4, 4, 4, 
	4, 4, 3, 4, 5, 5, 5, 4, 5, 1, 3, 3, 4, 5, 3, 4, NA, 5, 4, 3, 3, 3, 
	4, 3, 3, 3, 3), convsced = c(3, 3, 3, 4, 2, 5, 3, 3, 3, 4, 4, 3, 2,
	5, 3, 1, 4, 2, 5, 4, 5, 2, 5, 3, 4, 3, 5, 3, 4, 2, 3, 5, 3, 3, 4, 
	4, 3, 3, 4, 4, 5, 5, 4, 5, 1, 3, 3, 2, 3, 4, 3, NA, 5, 4, 4, 2, 4, 
	4, 3, 3, 2, 3), speed = c(3, 5, 4, 5, 2, 5, 3, 5, 4, 4, 4, 2, 4, 5,
	2, 3, 5, 4, 5, 4, 4, 5, 5, 5, 5, 4, 5, 3, 2, 4, 5, 5, 2, 4, 4, 5, 
	5, 4, 5, 4, 5, 5, 4, 5, 5, 3, 4, 5, 3, 4, 4, NA, 5, 3, 5, 5, 4, 3, 
	4, 3, 2, 3), frequenc = c(2, 4, 4, 5, 2, 4, 3, 3, 3, 4, 4, 4, 1, 5,
	3, 1, 4, 2, 5, 3, 3, 2, 5, 5, 5, 4, 5, 3, 2, 2, 3, 5, 2, 3, 3, 3, 
	3, 3, 5, 3, 5, 3, 4, 5, 1, 3, 3, NA, 3, 4, 3, NA, 4, 3, 4, 3, 3, 3,
	4, 3, 2, 3), tokenpur = c(3, 2, 1, 5, 5, 5, 3, 2, 5, 4, 4, 5, 4, 5,
	3, 2, 4, 5, 1, 4, 5, 5, 5, 2, 4, 3, 5, 3, 4, 3, 4, 3, 2, 2, 3, 5, 
	3, 4, 5, 2, 4, 4, 3, 4, 1, 4, 3, 5, 1, 5, 4, NA, 3, 4, 3, 3, 3, 3, 
	2, 3, 2, 2), tokencol = c(4, 3, 3, 4, 5, 5, 3, 2, 5, 4, 3, 4, 4, 5,
	3, 2, 4, 5, 3, 4, 5, 4, 5, 5, 5, 3, 5, 3, 5, 4, 4, 5, 2, 2, 3, 5, 
	3, 2, NA, 5, 5, 5, 3, 4, 5, 4, 3, 5, NA, 5, 4, NA, 3, 4, 4, 3, 3, 
	3, 4, 3, 2, 4), polstat = c(4, 2, 3, 5, 2, 1, 2, 2, 4, 3, 3, 4, 3, 
	3, 2, 1, 2, 1, 4, 2, 4, 2, 4, 2, 2, 3, 2, 3, 5, 3, 3, 2, 3, 3, 2, 
	3, 1, 3, 4, 3, 4, 3, 2, 3, 1, 3, 3, 1, 3, 4, 4, NA, 1, 2, 2, 1, 2, 
	3, 2, 1, 3, 3), poltrain = c(4, 3, 3, 4, 2, 1, 2, 2, 3, 2, 2, 2, 2,
	2, 2, 1, 2, 1, 4, 2, 1, 1, 3, 2, 2, 3, 2, 3, 5, 2, 2, 1, 1, 4, 1, 
	3, 1, 3, 4, 1, 3, 1, 2, 3, 1, 2, 4, 1, 2, 4, 3, NA, 1, 2, 1, 1, 1, 
	1, 2, 1, 3, 2), maps = c(5, 2, 4, 5, 5, 5, 3, 5, 5, 2, 5, 3, 4, 3, 
	3, 4, 2, 5, 5, 4, 4, 5, 5, 1, 4, 3, 5, 4, 5, 3, 3, 3, 4, 5, 3, 5, 
	3, 3, 4, NA, 2, 2, 4, 4, 1, 4, 3, 5, 4, 4, 4, NA, 3, 3, 1, 5, 3, 5,
	NA, 2, 3, 3), numbuse = c(20, 3, 10, 8, 10, 10, 5, 7, 8, 10, 0, 10,
	2, 10, 14, 13, 8, 12, 0, 3, 10, 0, 3, 2, 12, 10, 0, 4, 14, 10, 0, 
	5, 12, 10, 0, 2, 10, 9, 2, 5, 0, 12, 4, 8, 0, 2, 0, 0, 0, 0, 12, 8,
	12, 2, 0, 2, 10, 12, 4, 10, 0, 7)), class = "data.frame", 
	row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", 
	"11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", 
	"22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", 
	"33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", 
	"44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", 
	"55", "56", "57", "58", "59", "60", "61", "62"))
"vine1"<-
structure(.Data = list(row = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 
	14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30,
	31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47,
	48, 49, 50, 51, 52), lug1983 = c(5, 10, 11, 11.25, 11, 11, 9, 9, 9,
	9, 6, 7, 5, 7, 10, 13, 5.5, 10.5, 9, 6, 8, 15, 13, 14, 15, 14.5, 
	14, 14, 15, 16, 13, 12, 9, 11.5, 9.5, 12, 13, 13.5, 15, 15.5, 14, 
	14, 10, 13, 11, 8.5, 7.5, 6, 5, 4, 3, 2), lug1984 = c(5, 5, 11, 10,
	7, 13, 10.5, 10, 13, 12, 10, 9, 11, 7, 8, 10.5, 10, 11.5, 9, 11, 
	13, 15, 14, 17, 16, 14, 11, 16, 12, 11.5, 11, 13, 12, 12, 13, 9, 
	15, 12, 7, 7, 10, 5, 3.5, 5, 14, 13, 19, 11.5, 10, 6, 6.5, 5), 
	lug1985 = c(2, 5, 4, 5, 4, 3, 2.5, 2, 2, 2, 3, 2.5, 2, 3, 3, 3, 4, 
	5, 6, 8, 7, 11, 9, 10, 10, 11, 14, 15, 12, 10, 12, 13, 9.5, 8, 8, 
	9, 11, 13, 16, 18, 12, 15, 14, 20, 14, 7, 7.5, 4, 5, 3, 1.5, 0.5), 
	lug1986 = c(4.5, 9, 9, 9.5, 10, 7, 7.5, 7, 8, 7, 7, 5, 5, 4, 3, 4, 
	4, 4, 4.5, 3.5, 6, 5, 6, 6, 5, 7, 6, 5, 3, 5, 4, 4.5, 4, 4, 4, 4, 
	6, 6, 4, 3, 3.5, 8, 6, 4.5, 6, 4.5, 4, 3, 3, 2, 1, 0.5), lug1987
	 = c(1.5, 4, 6, 7, 7, 10, 7, 7, 10, 7, 6, 7, 9, 9, 8, 12, 13, 15, 
	17, 20, 16, 17, 15, 12, 13, 13, 18, 20, 16, 16, 16, 16, 15, 11, 11,
	11, 8.5, 10, 6, 10, 8, 8, 6, 8, 6, 6, 7, 3, 3, 2, 2, 2), lug1988
	 = c(1.5, 4, 6, 5, 6, 5, 5, 6, 8, 5, 8, 7, 10, 9, 9, 9, 7, 7, 7, 7,
	8, 9, 7, 8, 8, 8, 8, 8, 7, 7, 10, 8, 7, 7, 11, 11, 12, 10, 11, 11, 
	11, 8.5, 10, 9, 11, 7, 5, 3, 3, 1.5, 1, 0), lug1989 = c(1, 3, 3, 3,
	5, 3.5, 3, 4.5, 5, 5, 6, 5, 4, 6, 5, 6.5, 4, 6, 3, 6, 5, 8, 4.5, 4,
	4, 6.5, 4, 5, 3, 5.5, 3, 2, 2, 2, 2, 3, 2, 2, 2, 2, 2, 1.5, 1.5, 
	1.5, 1, 1, 1, 1, 0.5, 0.5, 0, 0), lug1990 = c(5, 8, 11, 9, 9.5, 10,
	12, 10, 11.5, 10, 11, 10, 10.5, 10, 11, 11, 11.5, 12, 12.5, 13, 11,
	11, 11, 13, 11, 13, 12, 14, 10, 13, 8, 7.5, 8, 8, 7, 10, 7, 10, 8, 
	10, 9, 10, 8, 11, 10, 7, 5, 7, 8, 6, 7.5, 2.5), lug1991 = c(9.5, 
	17.5, 18, 20, 20.5, 20, 19, 21, 19, 26, 20, 23, 22, 20, 20, 24, 23,
	23, 20, 21, 23, 23, 22, 22, 21, 20, 18, 21, 16, 16, 15, 16, 15, 15,
	17, 17, 21, 17, 20, 16, 20, 15, 17, 17, 20, 15, 14, 12, 11, 11, 
	8.5, 2.5)), class = "data.frame", row.names = c("1", "2", "3", "4",
	"5", "6", "7", "8", "9", "10", "11", "12", "13", "14", "15", "16", 
	"17", "18", "19", "20", "21", "22", "23", "24", "25", "26", "27", 
	"28", "29", "30", "31", "32", "33", "34", "35", "36", "37", "38", 
	"39", "40", "41", "42", "43", "44", "45", "46", "47", "48", "49", 
	"50", "51", "52"))
"vine2"<-
structure(.Data = list(year = c(1983, 1983, 1983, 1983, 1983, 1983, 1983, 
	1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 
	1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 
	1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 
	1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 1983, 
	1983, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 
	1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 
	1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 
	1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 
	1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1984, 1985, 1985, 
	1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 
	1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 
	1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 
	1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 1985, 
	1985, 1985, 1985, 1985, 1985, 1985, 1986, 1986, 1986, 1986, 1986, 
	1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 
	1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 
	1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 
	1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 1986, 
	1986, 1986, 1986, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 
	1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 
	1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 
	1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 
	1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 1987, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 
	1988, 1988, 1988, 1988, 1988, 1988, 1988, 1988, 1989, 1989, 1989, 
	1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 
	1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 
	1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 
	1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 1989, 
	1989, 1989, 1989, 1989, 1989, 1990, 1990, 1990, 1990, 1990, 1990, 
	1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 
	1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 
	1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 
	1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 1990, 
	1990, 1990, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 
	1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 
	1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 
	1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 
	1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991, 1991), row
	 = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
	19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
	36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,
	1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 
	20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36,
	37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 
	2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 1, 2, 
	3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 
	21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
	38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52), yield
	 = c(158.672, 317.34500000000004, 349.079, 357.01299999999996, 
	349.079, 349.079, 285.61, 285.61, 285.61, 285.61, 190.407, 222.141,
	158.672, 222.141, 317.34500000000004, 412.548, 174.53899999999998, 
	333.212, 285.61, 190.407, 253.876, 476.017, 412.548, 444.282, 
	476.017, 460.15, 444.282, 444.282, 476.017, 507.751, 412.548, 
	380.813, 285.61, 364.946, 301.47699999999996, 380.813, 412.548, 
	428.415, 476.017, 491.884, 444.282, 444.282, 317.34500000000004, 
	412.548, 349.079, 269.743, 238.008, 190.407, 158.672, 126.938, 
	95.203, 63.469, 154.597, 154.597, 340.11399999999996, 309.195, 
	216.436, 401.953, 324.654, 309.195, 401.953, 371.033, 309.195, 
	278.27499999999996, 340.11399999999996, 216.436, 247.356, 324.654, 
	309.195, 355.574, 278.27499999999996, 340.11399999999996, 401.953, 
	463.792, 432.872, 525.631, 494.711, 432.872, 340.11399999999996, 
	494.711, 371.033, 355.574, 340.11399999999996, 401.953, 371.033, 
	371.033, 401.953, 278.27499999999996, 463.792, 371.033, 216.436, 
	216.436, 309.195, 154.597, 108.218, 154.597, 432.872, 401.953, 
	587.47, 355.574, 309.195, 185.517, 200.976, 154.597, 60.187, 
	150.46799999999998, 120.374, 150.46799999999998, 120.374, 90.281, 
	75.234, 60.187, 60.187, 60.187, 90.281, 75.234, 60.187, 90.281, 
	90.281, 90.281, 120.374, 150.46799999999998, 180.561, 240.748, 
	210.655, 331.029, 270.842, 300.935, 300.935, 331.029, 421.309, 
	451.403, 361.122, 300.935, 361.122, 391.216, 285.88799999999996, 
	240.748, 240.748, 270.842, 331.029, 391.216, 481.496, 541.683, 
	361.122, 451.403, 421.309, 601.87, 421.309, 210.655, 225.701, 
	120.374, 150.46799999999998, 90.281, 45.14, 15.047, 144.118, 
	288.23700000000004, 288.23700000000004, 304.25, 320.26299999999996,
	224.184, 240.197, 224.184, 256.20999999999996, 224.184, 224.184, 
	160.132, 160.132, 128.10499999999998, 96.079, 128.10499999999998, 
	128.10499999999998, 128.10499999999998, 144.118, 112.092, 192.158, 
	160.132, 192.158, 192.158, 160.132, 224.184, 192.158, 160.132, 
	96.079, 160.132, 128.10499999999998, 144.118, 128.10499999999998, 
	128.10499999999998, 128.10499999999998, 128.10499999999998, 
	192.158, 192.158, 128.10499999999998, 96.079, 112.092, 
	256.20999999999996, 192.158, 144.118, 192.158, 144.118, 
	128.10499999999998, 96.079, 96.079, 64.053, 32.026000000000004, 
	16.013000000000002, 46.436, 123.829, 185.743, 216.7, 216.7, 
	309.572, 216.7, 216.7, 309.572, 216.7, 185.743, 216.7, 278.615, 
	278.615, 247.658, 371.486, 402.444, 464.358, 526.27200000000008, 
	619.144, 495.315, 526.27200000000008, 464.358, 371.486, 402.444, 
	402.444, 557.23, 619.144, 495.315, 495.315, 495.315, 495.315, 
	464.358, 340.529, 340.529, 340.529, 263.13600000000004, 309.572, 
	185.743, 309.572, 247.658, 247.658, 185.743, 247.658, 185.743, 
	185.743, 216.7, 92.872, 92.872, 61.914, 61.914, 61.914, 41.75, 
	111.332, 166.999, 139.166, 166.999, 139.166, 139.166, 166.999, 
	222.665, 139.166, 222.665, 194.832, 278.331, 250.498, 250.498, 
	250.498, 194.832, 194.832, 194.832, 194.832, 222.665, 250.498, 
	194.832, 222.665, 222.665, 222.665, 222.665, 222.665, 194.832, 
	194.832, 278.331, 222.665, 194.832, 194.832, 306.164, 306.164, 
	333.997, 278.331, 306.164, 306.164, 306.164, 236.582, 278.331, 
	250.498, 306.164, 194.832, 139.166, 83.499, 83.499, 41.75, 27.833, 
	0, 27.085, 81.255, 81.255, 81.255, 135.42500000000002, 94.798, 
	81.255, 121.883, 135.42500000000002, 135.42500000000002, 162.51, 
	135.42500000000002, 108.34, 162.51, 135.42500000000002, 176.053, 
	108.34, 162.51, 81.255, 162.51, 135.42500000000002, 216.68, 
	121.883, 108.34, 108.34, 176.053, 108.34, 135.42500000000002, 
	81.255, 148.96799999999998, 81.255, 54.17, 54.17, 54.17, 54.17, 
	81.255, 54.17, 54.17, 54.17, 54.17, 54.17, 40.628, 40.628, 40.628, 
	27.085, 27.085, 27.085, 27.085, 13.543, 13.543, 0, 0, 149.153, 
	238.645, 328.137, 268.476, 283.391, 298.307, 357.968, 298.307, 
	343.053, 298.307, 328.137, 298.307, 313.22199999999996, 298.307, 
	328.137, 328.137, 343.053, 357.968, 372.883, 387.799, 328.137, 
	328.137, 328.137, 387.799, 328.137, 387.799, 357.968, 417.63, 
	298.307, 387.799, 238.645, 223.73, 238.645, 238.645, 208.815, 
	298.307, 208.815, 298.307, 238.645, 298.307, 268.476, 298.307, 
	238.645, 328.137, 298.307, 208.815, 149.153, 208.815, 238.645, 
	178.984, 223.73, 74.577, 308.293, 567.908, 584.134, 649.038, 
	665.264, 649.038, 616.586, 681.49, 616.586, 843.749, 649.038, 
	746.393, 713.941, 649.038, 649.038, 778.845, 746.393, 746.393, 
	649.038, 681.49, 746.393, 746.393, 713.941, 713.941, 681.49, 
	649.038, 584.134, 681.49, 519.23, 519.23, 486.778, 519.23, 486.778,
	486.778, 551.682, 551.682, 681.49, 551.682, 649.038, 519.23, 
	649.038, 486.778, 551.682, 551.682, 649.038, 486.778, 454.326, 
	389.423, 356.971, 356.971, 275.841, 81.13)), class = "data.frame", 
	row.names = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", 
	"11", "12", "13", "14", "15", "16", "17", "18", "19", "20", "21", 
	"22", "23", "24", "25", "26", "27", "28", "29", "30", "31", "32", 
	"33", "34", "35", "36", "37", "38", "39", "40", "41", "42", "43", 
	"44", "45", "46", "47", "48", "49", "50", "51", "52", "53", "54", 
	"55", "56", "57", "58", "59", "60", "61", "62", "63", "64", "65", 
	"66", "67", "68", "69", "70", "71", "72", "73", "74", "75", "76", 
	"77", "78", "79", "80", "81", "82", "83", "84", "85", "86", "87", 
	"88", "89", "90", "91", "92", "93", "94", "95", "96", "97", "98", 
	"99", "100", "101", "102", "103", "104", "105", "106", "107", 
	"108", "109", "110", "111", "112", "113", "114", "115", "116", 
	"117", "118", "119", "120", "121", "122", "123", "124", "125", 
	"126", "127", "128", "129", "130", "131", "132", "133", "134", 
	"135", "136", "137", "138", "139", "140", "141", "142", "143", 
	"144", "145", "146", "147", "148", "149", "150", "151", "152", 
	"153", "154", "155", "156", "157", "158", "159", "160", "161", 
	"162", "163", "164", "165", "166", "167", "168", "169", "170", 
	"171", "172", "173", "174", "175", "176", "177", "178", "179", 
	"180", "181", "182", "183", "184", "185", "186", "187", "188", 
	"189", "190", "191", "192", "193", "194", "195", "196", "197", 
	"198", "199", "200", "201", "202", "203", "204", "205", "206", 
	"207", "208", "209", "210", "211", "212", "213", "214", "215", 
	"216", "217", "218", "219", "220", "221", "222", "223", "224", 
	"225", "226", "227", "228", "229", "230", "231", "232", "233", 
	"234", "235", "236", "237", "238", "239", "240", "241", "242", 
	"243", "244", "245", "246", "247", "248", "249", "250", "251", 
	"252", "253", "254", "255", "256", "257", "258", "259", "260", 
	"261", "262", "263", "264", "265", "266", "267", "268", "269", 
	"270", "271", "272", "273", "274", "275", "276", "277", "278", 
	"279", "280", "281", "282", "283", "284", "285", "286", "287", 
	"288", "289", "290", "291", "292", "293", "294", "295", "296", 
	"297", "298", "299", "300", "301", "302", "303", "304", "305", 
	"306", "307", "308", "309", "310", "311", "312", "313", "314", 
	"315", "316", "317", "318", "319", "320", "321", "322", "323", 
	"324", "325", "326", "327", "328", "329", "330", "331", "332", 
	"333", "334", "335", "336", "337", "338", "339", "340", "341", 
	"342", "343", "344", "345", "346", "347", "348", "349", "350", 
	"351", "352", "353", "354", "355", "356", "357", "358", "359", 
	"360", "361", "362", "363", "364", "365", "366", "367", "368", 
	"369", "370", "371", "372", "373", "374", "375", "376", "377", 
	"378", "379", "380", "381", "382", "383", "384", "385", "386", 
	"387", "388", "389", "390", "391", "392", "393", "394", "395", 
	"396", "397", "398", "399", "400", "401", "402", "403", "404", 
	"405", "406", "407", "408", "409", "410", "411", "412", "413", 
	"414", "415", "416", "417", "418", "419", "420", "421", "422", 
	"423", "424", "425", "426", "427", "428", "429", "430", "431", 
	"432", "433", "434", "435", "436", "437", "438", "439", "440", 
	"441", "442", "443", "444", "445", "446", "447", "448", "449", 
	"450", "451", "452", "453", "454", "455", "456", "457", "458", 
	"459", "460", "461", "462", "463", "464", "465", "466", "467", 
	"468"))
"vine3"<-
structure(.Data = list(year = c(1976, 1977, 1978, 1979, 1980, 1981, 1982, 
	1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990, 1991), lugs = c(11,
	476, 60, 102, 71, 203, 127, 534.75, 552.5, 401, 266, 514, 377.5, 
	170.5, 502, 940.5), yield = c(313, 13299, 1848, 2894, 1792, 5483, 
	3490, 16970, 17083, 12067.5, 8519, 15912, 10507, 4618, 14975, 
	30521), initial = c(NA, NA, NA, NA, NA, NA, NA, 44.25, 41, 16, 
	35.5, 30, 22, 14.5, 39.5, 78.5)), class = "data.frame", row.names
	 = c("1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12",
	"13", "14", "15", "16"))
"vote"<-
structure(.Data = list(year = c(1982, 1982, 1982, 1984, 1984, 1984, 1984, 
	1986, 1986, 1986, 1988, 1988, 1988, 1988, 1990, 1990, 1990, 1992, 
	1992, 1992, 1992, 1993), district = c(2, 4, 8, 1, 3, 5, 7, 2, 4, 8,
	1, 3, 5, 7, 2, 4, 8, 1, 3, 5, 7, 2), absdem = c(551, 594, 338, 
	1357, 716, 1207, 929, 609, 666, 477, 1101, 448, 781, 644, 660, 482,
	308, 1923, 695, 841, 814, 1396), absrep = c(205, 312, 115, 764, 
	144, 1436, 258, 316, 306, 171, 700, 70, 1610, 250, 509, 831, 148, 
	594, 327, 1275, 423, 371), machdem = c(47767, 44437, 55662, 58327, 
	78270, 54812, 77136, 39034, 52817, 48315, 56362, 69801, 43527, 
	68702, 27543, 39193, 34598, 65943, 58480, 41267, 65516, 19127), 
	machrep = c(21340, 28533, 13214, 38883, 6473, 55829, 13730, 23363, 
	16541, 11605, 34514, 3939, 56721, 12602, 26843, 27664, 8551, 21518,
	12968, 46967, 14310, 19691)), class = "data.frame", row.names = c(
	"1", "2", "3", "4", "5", "6", "7", "8", "9", "10", "11", "12", 
	"13", "14", "15", "16", "17", "18", "19", "20", "21", "22"))
"whale"<-
structure(.Data = list(period1 = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 
	13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29,
	30, 31, 32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46,
	47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63,
	64, 65, 66, 67, 68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
	81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97,
	98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108, 109, 110, 111,
	112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 123, 124, 
	125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 135, 136, 137, 
	138, 139, 140, 141, 142, 143, 144, 145, 146, 147, 148, 149, 150, 
	151, 152, 153, 154, 155, 156, 157, 158, 159, 160, 161, 162, 163, 
	164, 165, 166, 167, 168, 169, 170, 171, 172, 173, 174, 175, 176, 
	177, 178, 179, 180, 181, 182, 183, 184, 185, 186, 187, 188, 189, 
	190, 191, 192, 193, 194, 195, 196, 197, 198, 199, 200, 201, 202, 
	203, 204, 205, 206, 207, 208, 209, 210, 211, 212, 213, 214, 215, 
	216, 217, 218, 219, 220, 221, 222, 223, 224, 225, 226, 227, 228), 
	bouts1 = c(0, 0, 0, 0, 0, 4, 10, 9, 13, 9, 11, 10, 8, 9, 9, 7, 7, 
	8, 6, 4, 10, 7, 5, 7, 7, 8, 12, 8, 12, 10, 13, 6, 11, 11, 17, 11, 
	16, 10, 15, 8, 14, 6, 13, 16, 13, 13, 13, 11, 11, 8, 7, 6, 8, 9, 6,
	5, 6, 11, 8, 8, 12, 5, 8, 5, 6, 11, 11, 8, 4, 9, 6, 6, 12, 8, 14, 
	9, 13, 10, 12, 7, 12, 7, 6, 12, 8, 17, 10, 14, 12, 10, 8, 10, 7, 
	10, 6, 8, 10, 9, 10, 9, 11, 8, 12, 7, 11, 6, 10, 7, 7, 8, 11, 8, 
	10, 7, 9, 9, 9, 15, 6, 11, 8, 7, 10, 5, 10, 9, 10, 8, 6, 6, 12, 5, 
	4, 3, 6, 5, 4, 6, 2, 1, 3, 4, 4, 7, 7, 3, 8, 6, 2, 9, 4, 10, 7, 13,
	10, 6, 7, 7, 6, 10, 8, 12, 10, 8, 6, 5, 14, 4, 13, 3, 12, 9, 18, 
	10, 15, 10, 12, 10, 10, 12, 10, 6, 11, 6, 11, 7, 6, 6, 6, 3, 2, 12,
	6, 13, 10, 12, 9, 6, 4, 12, 6, 10, 7, 9, 12, 9, 10, 13, 11, 16, 12,
	10, 12, 5, 12, 10, 15, 15, 17, 6, 7, 11, 8, 11, 11, 11, 15, 10), 
	nursing1 = c(0, 0, 0, 0, 0, 26, 42, 143, 244, 137, 175, 181, 105, 
	190, 203, 202, 202, 162, 121, 121, 272, 248, 100, 230, 208, 198, 
	204, 222, 303, 379, 371, 155, 259, 384, 465, 383, 482, 157, 293, 
	211, 215, 93, 251, 286, 258, 262, 192, 298, 176, 95, 105, 86, 177, 
	184, 145, 129, 81, 167, 148, 128, 241, 51, 163, 119, 125, 253, 123,
	102, 39, 111, 102, 129, 196, 128, 198, 95, 166, 61, 133, 144, 167, 
	100, 97, 154, 126, 207, 154, 199, 187, 136, 150, 132, 138, 128, 
	125, 151, 144, 220, 172, 167, 165, 114, 158, 73, 144, 32, 130, 161,
	169, 142, 137, 139, 149, 135, 160, 290, 135, 173, 100, 137, 120, 
	100, 140, 132, 178, 139, 142, 107, 72, 55, 258, 49, 164, 42, 70, 
	57, 45, 72, 19, 8, 47, 78, 75, 148, 126, 43, 133, 84, 10, 117, 41, 
	23, 4, 127, 134, 94, 113, 132, 120, 114, 94, 96, 68, 40, 126, 95, 
	124, 60, 107, 24, 90, 169, 129, 62, 107, 62, 84, 61, 86, 179, 61, 
	72, 113, 91, 227, 44, 80, 65, 49, 110, 46, 78, 54, 149, 108, 252, 
	167, 81, 53, 102, 6, 109, 69, 213, 168, 93, 110, 81, 121, 68, 131, 
	96, 339, 59, 114, 127, 155, 195, 185, 23, 60, 126, 102, 165, 189, 
	182, 270, 252), lockons1 = c(0, 0, 0, 0, 0, 5, 11, 17, 33, 25, 37, 
	27, 21, 34, 32, 21, 17, 21, 12, 11, 33, 25, 11, 28, 16, 17, 25, 22,
	28, 30, 32, 14, 25, 30, 42, 40, 49, 21, 33, 22, 23, 11, 25, 30, 28,
	33, 27, 20, 17, 11, 10, 11, 12, 17, 9, 9, 7, 14, 9, 9, 17, 5, 11, 
	7, 9, 21, 14, 11, 4, 11, 7, 9, 15, 11, 22, 11, 17, 10, 12, 15, 17, 
	10, 10, 17, 12, 23, 15, 21, 16, 14, 10, 12, 9, 11, 8, 12, 16, 14, 
	14, 11, 14, 8, 14, 7, 12, 5, 11, 16, 11, 15, 17, 12, 17, 10, 15, 
	17, 11, 17, 8, 15, 11, 11, 12, 10, 16, 15, 14, 10, 5, 7, 23, 5, 15,
	4, 5, 7, 4, 10, 2, 1, 2, 10, 2, 17, 11, 2, 17, 10, 2, 17, 8, 5, 1, 
	22, 14, 14, 12, 11, 5, 14, 9, 16, 11, 8, 11, 11, 28, 9, 22, 5, 17, 
	22, 33, 20, 22, 19, 11, 17, 17, 22, 16, 16, 25, 14, 36, 11, 15, 14,
	11, 16, 7, 11, 17, 23, 22, 44, 28, 11, 7, 17, 5, 22, 8, 23, 36, 17,
	17, 21, 22, 22, 28, 15, 47, 8, 14, 22, 20, 37, 25, 5, 11, 20, 14, 
	16, 23, 20, 21, 28), daynight1 = c(0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1,
	0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 
	1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 
	0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 
	1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 
	0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 
	1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 
	0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 
	1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 
	0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 
	1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0), period2
	 = c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18,
	19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,
	36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52,
	53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69,
	70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86,
	87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100, 101, 102, 
	103, 104, 105, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 
	116, 117, 118, 119, 120, 121, 122, 123, 124, 125, 126, 127, 128, 
	129, 130, 131, 132, 133, 134, 135, 136, 137, 138, 139, 140, 141, 
	142, 143, 144, 145, 146, 147, 148, 149, 150, 151, 152, 153, 154, 
	155, 156, 157, 158, 159, 160, 161, 162, 163, 164, 165, 166, 167, 
	168, 169, 170, 171, 172, 173, 174, 175, 176, 177, 178, 179, 180, 
	181, 182, 183, 184, 185, 186, 187, 188, 189, 190, 191, 192, 193, 
	194, 195, 196, 197, 198, 199, 200, 201, 202, 203, 204, 205, 206, 
	207, 208, 209, 210, 211, 212, 213, 214, 215, 216, 217, 218, 219, 
	220, 221, 222, 223, NA, NA, NA, NA, NA), bouts2 = c(0, 0, 0, 9, 10,
	13, 9, 10, 10, 10, 10, 11, 14, 10, 7, 10, 11, 13, 10, 9, 7, 5, 7, 
	10, 12, 10, 11, 8, 13, 15, 14, 14, 14, 11, 11, 11, 14, 14, 11, 15, 
	13, 14, 11, 13, 15, 12, 13, 18, 18, 17, 13, 13, 15, 17, 11, 14, 12,
	11, 12, 10, 8, 12, 14, 12, 13, 11, 11, 8, 8, 8, 10, 10, 11, 11, 11,
	11, 9, 10, 11, 7, 8, 11, 8, 12, 9, 13, 9, 13, 10, 11, 8, 15, 12, 
	18, 15, 12, 4, 10, 14, 12, 10, 9, 8, 9, 9, 7, 14, 10, 12, 12, 10, 
	10, 14, 11, 8, 12, 15, 13, 11, 14, 15, 15, 13, 12, 13, 11, 8, 10, 
	8, 9, 8, 7, 10, 4, 12, 12, 24, 6, 15, 14, 12, 8, 18, 15, 12, 9, 9, 
	15, 12, 12, 9, 10, 12, 9, 11, 8, 10, 6, 8, 8, 7, 9, 6, 12, 9, 14, 
	12, 7, 12, 10, 12, 11, 12, 12, 12, 8, 10, 11, 14, 9, 13, 6, 11, 12,
	18, 9, 8, 12, 15, 11, 9, 12, 12, 12, 9, 14, 14, 15, 18, 11, 12, 15,
	8, 9, 12, 4, 8, 11, 16, 6, 8, 6, 8, 6, 7, 7, 10, 8, 12, 10, 7, 12, 
	2, NA, NA, NA, NA, NA), nursing2 = c(0, 0, 0, 59, 228, 260, 255, 
	538, 228, 485, 426, 693, 541, 509, 462, 813, 873, 756, 720, 497, 
	644, 371, 513, 470, 688, 737, 805, 450, 772, 954, 702, 613, 825, 
	537, 600, 491, 888, 605, 497, 419, 494, 524, 430, 444, 659, 442, 
	411, 590, 515, 440, 533, 445, 404, 362, 506, 353, 492, 344, 477, 
	411, 351, 409, 463, 377, 443, 344, 423, 200, 299, 204, 326, 292, 
	277, 380, 228, 226, 332, 228, 172, 284, 228, 180, 225, 216, 176, 
	252, 126, 528, 714, 435, 193, 565, 386, 694, 579, 464, 166, 308, 
	445, 432, 345, 253, 229, 196, 285, 225, 340, 349, 339, 473, 338, 
	433, 323, 156, 80, 441, 462, 453, 200, 449, 600, 750, 320, 429, 
	513, 191, 257, 275, 244, 359, 231, 232, 230, 104, 228, 299, 504, 
	174, 438, 372, 223, 267, 648, 444, 146, 360, 253, 446, 274, 169, 
	229, 239, 244, 104, 191, 98, 132, 92, 72, 98, 132, 198, 68, 167, 
	127, 135, 186, 218, 189, 205, 192, 199, 171, 192, 150, 175, 156, 
	137, 157, 93, 197, 48, 236, 160, 196, 69, 222, 308, 244, 98, 153, 
	456, 291, 126, 84, 172, 170, 218, 255, 144, 247, 271, 118, 275, 
	286, 104, 168, 275, 354, 96, 176, 74, 187, 51, 197, 85, 243, 119, 
	288, 495, 151, 870, 14, NA, NA, NA, NA, NA), lockons2 = c(0, 0, 0, 
	12, 28, 35, 22, 35, 27, 34, 27, 33, 33, 30, 28, 36, 33, 36, 34, 28,
	20, 16, 22, 21, 39, 33, 34, 12, 42, 55, 34, 32, 47, 30, 36, 36, 58,
	47, 35, 34, 42, 47, 35, 30, 47, 36, 30, 42, 47, 51, 44, 41, 40, 37,
	34, 36, 37, 33, 41, 32, 11, 23, 37, 27, 30, 28, 22, 20, 17, 17, 22,
	17, 25, 17, 25, 23, 16, 22, 22, 14, 17, 15, 16, 19, 14, 22, 11, 27,
	16, 28, 22, 36, 30, 42, 40, 37, 16, 30, 32, 34, 32, 21, 28, 21, 28,
	25, 25, 30, 28, 36, 30, 42, 40, 22, 11, 41, 36, 30, 22, 37, 33, 27,
	34, 28, 25, 30, 22, 22, 20, 14, 17, 11, 21, 10, 23, 28, 60, 16, 45,
	34, 23, 20, 66, 39, 17, 23, 22, 53, 30, 22, 22, 25, 39, 22, 25, 19,
	22, 15, 20, 23, 15, 33, 10, 28, 20, 23, 30, 22, 23, 28, 17, 30, 20,
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	16, 33, 25, 17, 11, 22, 25, 25, 39, 25, 27, 35, 23, 28, 30, 14, 20,
	32, 51, 17, 22, 14, 21, 11, 20, 19, 36, 27, 54, 20, 28, 11, 2, NA, 
	NA, NA, NA, NA), daynight2 = c(0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
	0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 
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	1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
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	1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
	0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 
	1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 
	0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 
	1, 0, 0, 1, 1, 0, 0, 1, 1, 0, 0, 1, 1, NA, NA, NA, NA, NA)), class
	 = "data.frame", row.names = c("1", "2", "3", "4", "5", "6", "7", 
	"8", "9", "10", "11", "12", "13", "14", "15", "16", "17", "18", 
	"19", "20", "21", "22", "23", "24", "25", "26", "27", "28", "29", 
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	"214", "215", "216", "217", "218", "219", "220", "221", "222", 
	"223", "224", "225", "226", "227", "228"))
