5 citations · 5 across the 1 of their papers we have counts for
2 papers
stat.ME2018★ 5 cited
Feature-specific inference for penalized regression using local false discovery rates
Ryan Miller, Patrick Breheny
Penalized regression methods, most notably the lasso, are a popular approach to analyzing high-dimensional data. An attractive property of the lasso is that it naturally performs v…
stat.ME2017
Marginal false discovery rate control for likelihood-based penalized regression models
Ryan Miller, Patrick Breheny
The popularity of penalized regression in high-dimensional data analysis has led to a demand for new inferential tools for these models. False discovery rate control is widely used…