2011•RePEc: Research Papers in EconomicsRequires access

LCLOGIT: Stata module to fit latent class conditional logit models via EM algorithm

Daniele Pacifico, Hong Il Yoo

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Abstract

lclogit fits latent class conditional logit models through an EM recursion proposed in Train (2008). The module can be useful to estimate nonparametric mixed logit models, as it allows to increase exponentially the number of mass points of each coefficient without compromising convergence.

About this research paper

What this paper is about

lclogit fits latent class conditional logit models through an EM recursion proposed in Train (2008). The module can be useful to estimate nonparametric mixed logit models, as it allows to increase exponentially the number of mass points of each coefficient without compromising convergence.

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Available abstract

lclogit fits latent class conditional logit models through an EM recursion proposed in Train (2008). The module can be useful to estimate nonparametric mixed logit models, as it allows to increase exponentially the number of mass points of each coefficient without compromising convergence.

Key concepts: Mixed logit, Logit, Recursion (computer science), Nonparametric statistics, Latent class model, Logistic regression, Convergence (economics), Class (philosophy)

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