SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models
Prabrisha Rakshit, Zhenyu Wang, T. Tony Cai, and Zijian Guo
We introduce the R package SIHR for statistical inference in high-dimensional generalized linear models with continuous and binary outcomes. The package provides functionalities for constructing confidence intervals and performing hypothesis tests for low-dimensional objectives in both one-sample and two-sample regression settings. We illustrate the usage of SIHR through numerical examples and present real data applications to demonstrate the package’s performance and practicality.