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? Basic MNL formulation
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
               ; Rhs = price, cntlngth, local, known, tod, seas $

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? Random parameters with two lognormal coefficients
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CREATE ; mseas = -seas ; mtod = -tod $
NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, mtod, mseas 
       ; RPL ; Pds = ntask ; Halton ; Pts = 50 ; Parameters 
       ; Fcn = cntlngth(n), local(n), known(n), mtod(l), mseas(l) $
CALC ; List ; exp ( b(4) + .5*b(10)^2) $  (This is for the coefficient on TOD)
CALC ; List ; exp ( b(5) + .5*b(11)^2) $  (This is for the coefficient on SEAS)
MATRIX ; bi_L = beta_i $

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? Random parameters with two one sided triangular coefficients
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, mtod, mseas 
       ; RPL ; Pds = ntask ; Halton ; Pts = 50 ; Parameters 
       ; Fcn = cntlngth(n), local(n), known(n), mtod(o), mseas(o) $
MATRIX ; bi_T = beta_i $

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? Kernel Estimators to look at conditional means of coefficients
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MATRIX ; bltod = bi_l(1:361,4:4) $  Lognormal TOD coefficients
MATRIX ; bttod = bi_t(1:361,4:4) $  Triangular coefficients
SAMPLE ; 1-361$                     Move coefficients to data area
CREATE ; bL = bltod $               by moving vector into a variable
CREATE ; bt = bttod $
KERNEL ; rhs = bl,bt 
       ; Title=Conditional Means of Random Coefficients on TOD $
SAMPLE ; all $ (Restore full sample)

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? Laatent Class Models
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 2 $
NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 3 $
NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 4 $

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? Two different classes, one with nonattendance to rate structure
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 2 
       ; RST = b1,b2,b3,b4,b5,b6, c1,c2,c3,c4,0,0 $

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? Formal attribute nonattendance
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 2 
       ; RST = b1,b2,b3,b4,b5,b6, b1,b2,b3,b4,0,0 $

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? Full attribute nonattendance.  2^K model
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NLOGIT ; Lhs = choice ; Choices = Firm1, Firm2, Firm3, Firm4
       ; Rhs = price, cntlngth, local, known, tod, seas 
       ; LCM ; Pds = ntask ; Pts = 4 
       ; RST = b1,b2,b3,b4,b5,b6, 
               b1,b2,b3,b4,0,  0,
               b1,b2,b3,b4,b5, 0,
               b1,b2,b3,b4, 0,b6 $