SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models
Abstract
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.
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