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Title:A geoadditive Bayesian latent variable model for Poisson indicators PDF Logo
Authors:Fahrmeir, Ludwig
Steinert, Sven
Issue Date:2006
Series/Report no.:Discussion paper // Sonderforschungsbereich 386 der Ludwig-Maximilians-Universität München 508
Abstract:We introduce a new latent variable model with count variable indicators, where usual linear parametric effects of covariates, nonparametric effects of continuous covariates and spatial effects on the continuous latent variables are modelled through a geoadditive predictor. Bayesian modelling of nonparametric functions and spatial effects is based on penalized spline and Markov random field priors. Full Bayesian inference is performed via an auxiliary variable Gibbs sampling technique, using a recent suggestion of Fr¨uhwirth-Schnatter and Wagner (2006). As an advantage, our Poisson indicator latent variable model can be combined with semiparametric latent variable models for mixed binary, ordinal and continuous indicator variables within an unified and coherent framework for modelling and inference. A simulation study investigates performance, and an application to post war human security in Cambodia illustrates the approach.
Subjects:Latent variable models
Poisson indicators
penalized splines
spatial effects
MCMC
Persistent Identifier of the first edition:urn:nbn:de:bvb:19-epub-1877-4
Document Type:Working Paper
Appears in Collections:Discussion papers, SFB 386, LMU München

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