pemultinom: L1-Penalized Multinomial Regression with Statistical Inference
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."
| Version: |
0.1.1 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
foreach, doParallel, stats, Rcpp, nnet, magrittr, utils, lpSolve |
| LinkingTo: |
Rcpp |
| Suggests: |
knitr, rmarkdown |
| Published: |
2025-02-28 |
| DOI: |
10.32614/CRAN.package.pemultinom |
| Author: |
Ye Tian [aut, cre],
Henry Rusinek [aut],
Arjun V. Masurkar [aut],
Yang Feng [aut] |
| Maintainer: |
Ye Tian <ye.t at columbia.edu> |
| License: |
GPL-2 |
| NeedsCompilation: |
yes |
| CRAN checks: |
pemultinom results |
Documentation:
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