SIHR: Statistical Inference in High-Dimensional Linear and Logistic Regression Models
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 simulated examples and present real data applications to demonstrate the package's performance and practicality.
Authors
- Zijian Guo (ORCID: https://orcid.org/0000-0003-4986-9308)
- Prabrisha Rakshit
- Zhenyu Wang (ORCID: https://orcid.org/0000-0003-3807-8623)
- Tommaso Cai (ORCID: https://orcid.org/0000-0002-7234-3526)
Institutions
- Rutgers, The State University of New Jersey (US)
- California University of Pennsylvania (US)
Publication Details
- Journal
- The R Journal
- Published
- 2025-05-20
- DOI
- https://doi.org/10.32614/rj-2024-028
- Primary Topic
- Advanced Statistical Methods and Models
- Type
- article
- Field-Weighted Citation Impact
- 0.00