pboost: Profile Boosting Framework for Parametric Models

Read full text
Authors: Zengchao Xu
Cited by: 0
References: 4

Abstract

A profile boosting framework for feature selection in parametric models. It offers a unified interface pboost() and several wrapped models, including linear model, generalized linear models, quantile regression, Cox proportional hazards model, beta regression. An S3 interface EBIC() is provided as the stopping rule for the profile boosting by default.

Publication details

Publication date
8 January 2026
Document type
Dataset