A Fully Bayesian Analysis of Multivariate Latent Class Models with an Application to Metric Conjoint Analysis

In this paper we head for a fully Bayesian analysis of the latent class model with a priori unknown number of classes. Estimation is carried out by means of Markov Chain Monte Carlo (MCMC) methods. We deal explicitely with the consequences the unidentifiability of this type of model has on MCMC estimation.(...)

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Year of publication:	2002-06-01
Authors:	Frühwirth-Schnatter, Sylvia ; Otter, Thomas ; Tüchler, Regina
Publisher:	Wirtschaftsuniversität <Wien>
Subject:	Conjoint Measurement \| Markov-Ketten-Monte-Carlo-Verfahren \| Markov-Chain Monte Carlo \| Bayes-Verfahren \| Latent-Class-Analyse \| latent class analysis

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Extent:	2048 bytes 21 p. application/pdf
Series:	Universitätsbibliothek Wien - Working Papers Working Papers SFB Adaptive Information Systems and Modelling in Economics and Management Science ; 2002, 89
Type of publication:	Book / Working Paper
Language:	English
Classification:	Forecast, decision making ; Decision Theory. Other ; Individual Working Papers, Preprints ; No country specification
Source:	USB Cologne (business full texts)

Persistent link: https://ebvufind01.dmz1.zbw.eu/10005844780