153 citations · 160 across the 5 of their papers we have counts for
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stat.ME2026
Global Inference for High Dimensional Quantile Regression with Heterogeneity
Tate Jacobson, Daeyoung Ham, Ben Sherwood
Quantile regression has received considerable attention in high dimensional methodology due to its robustness and ability to accommodate heteroskedasticity. Despite this attention,…
stat.ME2021
On the Use of Minimum Penalties in Statistical Learning
Ben Sherwood, Bradley S. Price
Modern multivariate machine learning and statistical methodologies estimate parameters of interest while leveraging prior knowledge of the association between outcome variables. Th…
stat.ME2015
Variable Selection for Additive Partial Linear Quantile Regression with Missing Covariates
Ben Sherwood
The standard quantile regression model assumes a linear relationship at the quantile of interest and that all variables are observed. We relax these assumptions by considering a pa…