Metadata-Version: 2.4
Name: boxhed
Version: 2.0.13
Summary: BoXHED2.0
Author: Arash Pakbin, Bobak Mortazavi, and Donald K K Lee
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: scikit-learn
Requires-Dist: matplotlib
Requires-Dist: tqdm
Requires-Dist: py3nvml
Requires-Dist: boxhed_kernel
Requires-Dist: boxhed_prep
Dynamic: author
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

**B**oosted e**X**act **H**azard **E**stimator with **D**ynamic covariates v2.0 (BoXHED2.0, pronounced 'box-head') is a software package for nonparametrically estimating hazard functions via gradient boosted trees. BoXHED2.0 accommodates both time-static and time-dependent covariates.

Please refer to the [BoXHED2.0 paper](https://doi.org/10.18637/jss.v113.i03) (Journal of Statistical Software 113:3, 2025) for details, which builds on the [BoXHED1.0 paper](http://proceedings.mlr.press/v119/wang20o/wang20o.pdf) (ICML 2020). The theoretical underpinnings for BoXHED is provided [here](https://projecteuclid.org/journals/annals-of-statistics/volume-49/issue-4/Boosted-nonparametric-hazards-with-time-dependent-covariates/10.1214/20-AOS2028.full) (The Annals of Statistics 2021). 

A tutorial notebook can be found at this [GitHub page](https://github.com/BoXHED/BoXHED2.0).
