BoXHED2.0: Scalable Boosting of Dynamic Survival Analysis
Dublin Core
Title
BoXHED2.0: Scalable Boosting of Dynamic Survival Analysis
Description
Modern applications of survival analysis increasingly involve time-dependent covariates.The Python package BoXHED2.0 (Boosted eXact Hazard Estimator with Dynamic covariates) is a tree-boosted hazard estimator that is fully nonparametric, and is applicable to survival settings far more general than right-censoring, including recurring events and competing risks. BoXHED2.0 is also scalable to the point of being on the same order of speed as parametric boosted survival models, in part because its core is written in C++ and it also supports the use of GPUs and multicore CPUs. BoXHED2.0 is available from PyPI and also from https://github.com/BoXHED.
Creator
Arash Pakbin, Xiaochen Wang, Bobak J. Mortazavi, Donald K. K. Lee
Source
https://www.jstatsoft.org/article/view/v113i03
Publisher
OJS/PKP
Date
28 JULI 2025
Contributor
FAJAR BAGUS W
Format
PDF
Language
ENGLISH
Type
TEXT
Files
Collection
Citation
Arash Pakbin, Xiaochen Wang, Bobak J. Mortazavi, Donald K. K. Lee, “BoXHED2.0: Scalable Boosting of Dynamic Survival Analysis,” Repository Horizon University Indonesia, accessed January 11, 2026, https://repository.horizon.ac.id/items/show/9933.