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Bayesian inference for factor structure models via gibbs sampling
[working paper]
Corporate Editor
Universität Konstanz, Center for Quantitative Methods and Survey Research (CMS)
Abstract
"The goal of this paper is to provide all the technical details required to implement Gibbs sampling for the estimation of simultaneous equation models with common latent factors among their regressors, so-called "factor structure models". Linear, dichotomous and censored response models, as well as... view more
"The goal of this paper is to provide all the technical details required to implement Gibbs sampling for the estimation of simultaneous equation models with common latent factors among their regressors, so-called "factor structure models". Linear, dichotomous and censored response models, as well as ordered and unordered response models can be accommodated in this framework. The latent factors can be either correlated or not, and specified as normally distributed or as following a finite mixture of normal distributions for more flexibility. All conditional distributions are derived and can be used to construct the Gibbs sampler step by step." (author's abstract)... view less
Keywords
factor analysis; model analysis; social science; economics; statistical method; indicator; estimation
Classification
Sociology of Economics
Document language
English
Publication Year
2010
City
Konstanz
Page/Pages
26 p.
Series
CMS Discussion Paper, 3
Status
Published Version; reviewed
Licence
Deposit Licence - No Redistribution, No Modifications
Data providerThis metadata entry was indexed by the Special Subject Collection Social Sciences, USB Cologne