Approximations of choice probabilities in mixed logit models

N. Kalouptsidis and V. Psaraki

European Journal of Operational Research, 2010, vol. 200, issue 2, pages 529-535

Abstract: This paper is concerned with the approximate computation of choice probabilities in mixed logit models. The relevant approximations are based on the Taylor expansion of the classical logit function and on the high order moments of the random coefficients. The approximate choice probabilities and their derivatives are used in conjunction with log likelihood maximization for parameter estimation. The resulting method avoids the assumption of an apriori distribution for the random tastes. Moreover experiments with simulation data show that it compares well with the simulation based methods in terms of computational cost.

Keywords: Discrete; choice; Random; utility; maximization; models; Approximate; choice; probabilities; Mixed; logit (search for similar items in EconPapers)
Date: 2010

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Persistent link: http://EconPapers.repec.org/RePEc:eee:ejores:v:200:y:2010:i:2:p:529-535

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