lclogit : A Stata Module for Estimating a Mixed Logit Model with Discrete Mixing Distribution Via the Expectation-Maximization Algorithm

This paper describe lclogit, a Stata module to fit latent class logit models through the Expectation-Maximization algorithm. The stability of this estimation method allows overcoming some of the computational difficulties that normally arise when fitting such models with many latent classes. This, in turn, permits users to estimate nonparameterically the mixing distribution of the random coefficients because the more the mass points of the latent class model, the better the approximation of the unknown joint density of the random coefficients

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Year of publication:	2013
Authors:	Pacifico, Daniele
Other Persons:	Yoo, Hong Il (contributor)
Publisher:	[2013]: [S.l.] : SSRN
Subject:	Logit-Modell \| Logit model \| Theorie \| Theory \| Algorithmus \| Algorithm \| Diskrete Entscheidung \| Discrete choice

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