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A Recent Approach to Derive the Multinomial Logit Model for Choice Probability

Capitolo di libro
Data di Pubblicazione:
2018
Abstract:
It is well known that the Multinomial Logit model for the choice probability can be obtained by considering a random utility model where the choice variables are independent and identically distributed with a Gumbel distribution. In this paper we organize and summarize existing results of the literature which show that using some results of the extreme values theory for i.i.d. random variables, the Gumbel distribution for the choice variables is not necessary anymore and any distribution which is asymptotically exponential in its tail is sufficient to obtain the Multinomial Logit model for the choice probability.
Tipologia CRIS:
2.1 Contributo in volume (Capitolo o Saggio)
Keywords:
Random utility; Extreme values theory; Asymptotic approximation; Multinomial Logit model
Elenco autori:
Tadei, Roberto; Perboli, Guido; Manerba, Daniele
Autori di Ateneo:
MANERBA Daniele
Modelli e Algoritmi di Ottimizzazione
Link alla scheda completa:
https://iris.unibs.it/handle/11379/526345
Titolo del libro:
New Trends in Emerging Complex Real Life Problems
Pubblicato in:
AIRO SPRINGER SERIES
Series
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