Skinny Gibbs: A Consistent and Scalable Gibbs Sampler for Model Selection

DOI10.1080/01621459.2018.1482754zbMath1428.62116OpenAlexW2806706576MaRDI QIDQ5242469

Xuming He, Juan Shen, Naveen Naidu Narisetty

Publication date: 12 November 2019

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/01621459.2018.1482754

zbMATH Keywords

logistic regressionhigh-dimensional dataGibbs samplingvariable selectionBayesian computationscalable computation

Mathematics Subject Classification ID

Bayesian inference (62F15) Generalized linear models (logistic models) (62J12)

Related Items

Posterior contraction in group sparse logit models for categorical responses, Bayesian high-dimensional semi-parametric inference beyond sub-Gaussian errors, Bayesian group selection in logistic regression with application to MRI data analysis, Neuronized Priors for Bayesian Sparse Linear Regression, Discussion, Variable selection for partially linear models via Bayesian subset modeling with diffusing prior, Bayesian Bootstrap Spike-and-Slab LASSO

Uses Software

• SSS
• glmnet
• pi-MASS
• EMVS

Cites Work

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