Bayesian group Lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies

DOI10.1214/15-AOAS808zbMath1397.62260arXiv1509.04017WikidataQ36161135 ScholiaQ36161135MaRDI QIDQ746650

Zhong Wang, Jiahan Li, Rongling Wu, Run-Ze Li

Publication date: 28 October 2015

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

Full work available at URL: https://arxiv.org/abs/1509.04017

zbMATH Keywords

longitudinal dataGWASgroup variable selectionBayesian approach

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Ridge regression; shrinkage estimators (Lasso) (62J07) Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items

Bayesian variable selection for post‐analytic interrogation of susceptibility loci, Fast Markov Chain Monte Carlo for High-Dimensional Bayesian Regression Models With Shrinkage Priors, Semiparametric Bayesian multiple imputation for regression models with missing mixed continuous-discrete covariates, Robust Bayesian Variable Selection for Gene–Environment Interactions, Bayesian group Lasso for nonparametric varying-coefficient models with application to functional genome-wide association studies, Sparse linear mixed model selection via streamlined variational Bayes

Uses Software

• fda (R)
• BayesDA
• ElemStatLearn
• SNPinfo

Cites Work

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• The Bayesian Lasso
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