False discovery control for penalized variable selections with high-dimensional covariates
False discovery control for penalized variable selections with high-dimensional covariates
Abstract Modern bio-technologies have produced a vast amount of high-throughput data with the number of predictors much exceeding the sample size. Penalized variable selection has emerged as a powerful and efficient dimension reduction tool. However, control of false discoveries (i.e. inclusion of irrelevant variables) for penalized high-dimensional variable selection presents …