Quotation Tüchler, Regina. 2008. Bayesian variable selection for logistic models using auxiliary mixture sampling. Journal of Computational and Graphical Statistics (17): 76-94.


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Abstract

The paper presents an Markov Chain Monte Carlo algorithm for both variable and covariance selection in the context of logistic mixed effects models. This algorithm allows us to sample solely from standard densities, with no additional tuning being needed. We apply a stochastic search variable approach to select explanatory variables as well as to determine the structure of the random effects covariance matrix. For logistic mixed effects models prior determination of explanatory variables and random effects is no longer prerequisite since the definite structure is chosen in a data-driven manner in the course of the modeling procedure. As an illustration two real-data examples from finance and tourism studies are given.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Computational and Graphical Statistics
Citation Index SCI
WU-Journal-Rating new FIN-A, VW-C
Language English
Title Bayesian variable selection for logistic models using auxiliary mixture sampling
Number 17
Year 2008
Page from 76
Page to 94
Reviewed? Y
URL http://epub.wu-wien.ac.at/dyn/virlib/wp/eng/mediate/epub-wu-01_94d.pdf?ID=epub-wu-01_94d

Associations

People
Tüchler, Regina (Former researcher)
Organization
Institute for Statistics and Mathematics IN (Details)
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