Grün, Bettina and Leisch, Friedrich
Identifiability of Finite Mixtures of Multinomial Logit Models with Varying and Fixed Effects.
Department of Statistics: Technical Reports, No.24
Unique parametrizations of models are very important for parameter
interpretation and consistency of estimators. In this paper we analyze
the identifiability of a general class of finite mixtures of
multinomial logits with varying and fixed effects, which includes the
popular multinomial logit and conditional logit models. The
application of the general identifiability conditions is demonstrated
on several important special cases and relations to previously
established results are discussed. The main results are illustrated
with a simulation study using artificial data and a marketing dataset
of brand choices.