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pemultinom (version 0.1.1)

L1-Penalized Multinomial Regression with Statistical Inference

Description

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."

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Version

Install

install.packages('pemultinom')

Monthly Downloads

192

Version

0.1.1

License

GPL-2

Maintainer

Ye Tian

Last Published

February 28th, 2025

Functions in pemultinom (0.1.1)

debiased_lasso

Doing statistical inference on l1-penalized multinomial regression via debiased Lasso (or desparisified Lasso).
cv.pemultinom

Fit a multinomial regression model with Lasso penalty.
predict_pemultinom

Make predictions on new predictors based on fitted l1-penalized multinomial regression model.