Bayesian variable selection for finite mixture model of linear regressions

DOI10.1016/J.CSDA.2015.09.005zbMath1468.62112OpenAlexW1881193884MaRDI QIDQ1659475

Ying Nian Wu, Kuo-Jung Lee, Ray-Bing Chen

Publication date: 15 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2015.09.005

zbMATH Keywords

Gibbs samplersparsitystochastic search variable selectionmedian probability criterion

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Linear regression; mixed models (62J05) Bayesian inference (62F15)

Related Items (7)

Robust variable selection in finite mixture of regression models using the t distribution ⋮ Estimation and variable selection for mixture of joint mean and variance models ⋮ Bayesian variable selection in a finite mixture of linear mixed-effects models ⋮ A data-driven reversible jump for estimating a finite mixture of regression models ⋮ Variable selection for skew-normal mixture of joint location and scale models ⋮ Bayesian variable selection in linear regression models with non-normal errors ⋮ Variable selection in finite mixture of regression models using the skew-normal distribution

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