Quotation Zens, Gregor. 2019. Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership. Advances in Data Analysis and Classification. 13 (4), 1019-1051.


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Abstract

A method for implicit variable selection in mixture-of-experts frameworks is proposed. We introduce a prior structure where information is taken from a set of independent covariates. Robust class membership predictors are identified using a normal gamma prior. The resulting model setup is used in a finite mixture of Bernoulli distributions to find homogenous clusters of women in Mozambique based on their information sources on HIV. Fully Bayesian inference is carried out via the implementation of a Gibbs sampler.

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Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Advances in Data Analysis and Classification
Citation Index SCI
Language English
Title Bayesian shrinkage in mixture-of-experts models: identifying robust determinants of class membership
Volume 13
Number 4
Year 2019
Page from 1019
Page to 1051
Reviewed? Y
URL https://link.springer.com/article/10.1007/s11634-019-00353-y
DOI http://dx.doi.org/10.1007/s11634-019-00353-y
Open Access Y
Open Access Link https://link.springer.com/article/10.1007/s11634-019-00353-y
JEL 62F15, 62J07, 62H30, 90-08

Associations

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Zens, Gregor (Details)
Organization
Department of Economics (Crespo Cuaresma) (Details)
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