ArticleJournal of biometrics & biostatistics2013
Bayesian Methods for High Dimensional Linear Models.
Article in Journal of biometrics & biostatistics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
- Bayesian feature selection in joint models with application to a cardiovascular disease cohort study.Statistical methods in medical research · 2026Article
- Is Seeing Believing? A Practitioner's Perspective on High-Dimensional Statistical Inference in Cancer Genomics Studies.Entropy (Basel, Switzerland) · 2024Review
- Spike-and-slab least absolute shrinkage and selection operator generalized additive models and scalable algorithms for high-dimensional data analysis.Statistics in medicine · 2022Article
- Bayesian regularization for a nonstationary Gaussian linear mixed effects model.Statistics in medicine · 2022Article
- A novel 14-gene signature for overall survival in lung adenocarcinoma based on the Bayesian hierarchical Cox proportional hazards model.Scientific reports · 2022Article
- Bayesian estimation of subset threshold autoregressions: short-term forecasting of traffic occupancy.Journal of applied statistics · 2020Article
- Correlates of Alcohol Consumption and Drug Injection among Homeless Youth: A Case Study in the Southeast of Iran.Addiction & health · 2019Article
- Model-based clustering for identifying disease-associated SNPs in case-control genome-wide association studies.Scientific reports · 2019Article
- Bayesian imputation of time-varying covariates in linear mixed models.Statistical methods in medical research · 2019Article
- Spatial Signal Detection Using Continuous Shrinkage Priors.Technometrics : a journal of statistics for the physical, chemical, and engineering sciences · 2019Article
- Tractable Bayesian variable selection: beyond normality.Journal of the American Statistical Association · 2018Article
- Bayesian inference for biomarker discovery in proteomics: an analytic solution.EURASIP journal on bioinformatics & systems biology · 2017Article
- A Bayesian method for detecting pairwise associations in compositional data.PLoS computational biology · 2017Article
- Quality of life in idiopathic intracranial hypertension at diagnosis: IIH Treatment Trial results.Neurology · 2015Article
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Authors and funding
2 authors.
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Abstract
In this article, we present a selective overview of some recent developments in Bayesian model and variable selection methods for high dimensional linear models. While most of the reviews in literature are based on conventional methods, we focus on recently developed methods, which have proven to be successful in dealing with high dimensional variable selection. First, we give a brief overview of the traditional model selection methods (viz. Mallow's Cp, AIC, BIC, DIC), followed by a discussion on some recently developed methods (viz. EBIC, regularization), which have occupied the minds of many statisticians. Then, we review high dimensional Bayesian methods with a particular emphasis on Bayesian regularization methods, which have been used extensively in recent years. We conclude by briefly addressing the asymptotic behaviors of Bayesian variable selection methods for high dimensional linear models under different regularity conditions.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.