Generalized ExtremeValue Model
McFadden (1978) introduced the generalized extremevalue (GEV) distribution defined by
F(€ue2,. . . ,ej (9.3.67)
= exp {—(/[exp (eO, exp (e2), . . . , exp ( Cm)]), where G satisfies the conditions,
(i) 
G(ux, u2,. . . 
., мт) ё 0, 
«і, «2. • • • > мтё0. 
(ІІ) 
G(olu1,olu2, 
. . ., aum) 
= otG(ux, u2,. . ., uj. 
(iii) 
> A 
if к is odd if к is even, k= 1, 

duhduh. . . 
_ != U dulk SO 
If Uj — fij + €j and the alternative with the highest utility is chosen as before, (9.3.67) implies the GEV model
„ exp {/ii)G,[ep (fij), exp (fi2. . ., exp (jMm)]
/УТ / / /  > (У. З.Оо)
3 (/[exp (fj. il exp (fj2),. . ., exp (yUm)]
where Gj is the derivative of G with respect to its yth argument.
Both the nested logit model and the higher...
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