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The Stata Journal
Volume 12 Number 2: pp. 284-298

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Fitting nonparametric mixed logit models via expectation-maximization algorithm

Daniele Pacifico
Italian Department of the Treasury
Rome, Italy
daniele.pacifico@tesoro.it
Abstract.  In this article, I provide an illustrative, step-by-step implementation of the expectation–maximization algorithm for the nonparametric estimation of mixed logit models. In particular, the proposed routine allows users to fit straight-forwardly latent-class logit models with an increasing number of mass points so as to approximate the unobserved structure of the mixing distribution.

View all articles by this author: Daniele Pacifico

View all articles with these keywords: latent classes, expectation-maximization algorithm, nonparametric mixed logit

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