L1-Penalized Multinomial Regression with Statistical Inference
Overview
We aim for fitting a multinomial regression model with Lasso penalty and doing statistical inference (calculating confidence intervals of coefficients and p-values for individual variables). It implements 1) the coordinate descent algorithm to fit an l1-penalized multinomial regression model (parameterized with a reference level); 2) the debiasing approach to obtain the inference results, which is described in "Tian, Y., Rusinek, H., Masurkar, A. V., & Feng, Y. (2024). L1‐Penalized Multinomial Regression: Estimation, Inference, and Prediction, With an Application to Risk Factor Identification for Different Dementia Subtypes. Statistics in Medicine, 43(30), 5711-5747."
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 3
- Examples that run
- 67%2 run in a plain check · 1 only when donttest examples are enabled (R CMD check --as-cran)
- Exported functions with examples
- 100%
- Documented parameters
- 96%
- Return-value docs
- 100%
- Help pages citing references
- 100%
Downloads
Dependencies
Installing pemultinom adds 6 packages (3 with compiled code, 3.0 MB of source tarballs). Heaviest: Rcpp 1.8 MB, lpSolve 457 KB, iterators 293 KB.
Code & Tests
People & History
Pick two releases to compare their code metrics.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- 0.1.1Latest
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.02023-02-16
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2023-02-16
- Total releases
- 2 / 3 yrs
- License
- GPL-2 OSI
- Minimum R
- ≥ 3.5.0
- Download size
- 19 KB
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