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Robust Bayesian high-dimensional variable selection and inference with the horseshoe family of priors
Kun Fan, Srijana Subedi, Vishmi Ridmika Dissanayake Pathiranage +1
Frequentist robust variable selection has been extensively investigated in high-dimensional regression. Despite success, developing the corresponding statistical inference procedur…
The Spike-and-Slab Quantile LASSO for Robust Variable Selection in Cancer Genomics Studies
Yuwen Liu, Jie Ren, Shuangge Ma +1
Data irregularity in cancer genomics studies has been widely observed in the form of outliers and heavy-tailed distributions in the complex traits. In the past decade, robust varia…
Sparse group variable selection for gene-environment interactions in the longitudinal study
Fei Zhou, Xi Lu, Jie Ren +3
Penalized variable selection for high dimensional longitudinal data has received much attention as accounting for the correlation among repeated measurements and providing addition…
Identifying Gene-environment interactions with robust marginal Bayesian variable selection
Xi Lu, Kun Fan, Jie Ren +1
In high-throughput genetics studies, an important aim is to identify gene-environment interactions associated with the clinical outcomes. Recently, multiple marginal penalization m…
Robust Bayesian variable selection for gene-environment interactions
Jie Ren, Fei Zhou, Xiaoxi Li +3
Gene-environment (GE) interactions have important implications to elucidate the etiology of complex diseases beyond the main genetic and environmental effects. Outliers and…
Semi-parametric Bayesian variable selection for gene-environment interactions
Jie Ren, Fei Zhou, Xiaoxi Li +5
Many complex diseases are known to be affected by the interactions between genetic variants and environmental exposures beyond the main genetic and environmental effects. Study of…