Review of Bayesian selection methods for categorical predictors using JAGS

DOI10.1080/02664763.2021.1902955OpenAlexW3137143073MaRDI QIDQ5093004

Christine Hatte, Rana Jreich, Eric Parent

Publication date: 26 July 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2021.1902955

zbMATH Keywords

sparsityspike and slab priorsJAGScategorical predictorsBayesian selection methodsfusion regression effects

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• WinBUGS
• JAGS
• OpenBUGS
• Stan
• R2jags

Cites Work

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• Penalized regression, standard errors, and Bayesian Lassos
• Applied Bayesian Statistics
• Bootstrapping Lasso Estimators
• Mixture Densities, Maximum Likelihood and the EM Algorithm
• Bayesian Variable Selection in Linear Regression
• The Effect of Improper Priors on Gibbs Sampling in Hierarchical Linear Mixed Models
• Variable Selection via Nonconcave Penalized Likelihood and its Oracle Properties
• Sparsity and Smoothness Via the Fused Lasso
• Sharp Thresholds for High-Dimensional and Noisy Sparsity Recovery Using $\ell _{1}$-Constrained Quadratic Programming (Lasso)
• Effect fusion using model-based clustering
• Model Selection and Estimation in Regression with Grouped Variables

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