Modern applications of survival analysis increasingly involve time-dependent covariates. The Python package BoXHED2.0 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 www.github.com/BoXHED.

翻译：现代生存分析的应用日益涉及时间相依协变量。Python软件包BoXHED2.0是一种完全非参数的树提升风险估计器，适用于比右删失更广泛的生存分析场景，包括重复事件和竞争风险。BoXHED2.0的可扩展性已达到与参数化提升生存模型相当的速度水平，部分原因在于其核心采用C++编写，并支持GPU和多核CPU的使用。BoXHED2.0可从PyPI及www.github.com/BoXHED获取。