A review of Bayesian group selection approaches for linear regression models-Reference-Cited by-同舟云学术

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A review of Bayesian group selection approaches for linear regression models

Published:2020-06-29 Issue: Volume: Page:
ISSN:1939-5108
Container-title:WIREs Computational Statistics
language:en
Short-container-title:WIREs Comp Stat

Author:

Lai Wei‐Ting¹,Chen Ray‐Bing¹^ORCID

Affiliation:

1. Department of StatisticsNational Cheng Kung University Tainan Taiwan

Funder

Ministry of Science and Technology

National Center of Theoretical Sciences, Math Division

Publisher

Wiley

Subject

Statistics and Probability

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1513

Reference29 articles.

1. Optimal predictive model selection

2. A Two-Stage Bayesian Model Selection Strategy for Supersaturated Designs

3. Bayesian Variable Selections for Probit Models with Componentwise Gibbs Samplers

4. Stochastic matching pursuit for Bayesian variable selection

5. Bayesian Sparse Group Selection

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1. A Bayesian group selection with compositional responses for analysis of radiologic tumor proportions and their genomic determinants;The Annals of Applied Statistics;2023-12-01

2. Bayesian Approaches in Exploring Gene-environment and Gene-gene Interactions: A Comprehensive Review;Cancer Genomics - Proteomics;2023-11-30

3. Indicator-based Bayesian variable selection for Gaussian process models in computer experiments;Computational Statistics & Data Analysis;2023-09

4. Multinomial logistic regression classifier via lq,0-proximal Newton algorithm;Neurocomputing;2022-01

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