NEWS.md

In stochtree: Stochastic Tree Ensembles (XBART and BART) for Supervised Learning and Causal Inference

stochtree 0.1.0

• Initial release on CRAN.
• Support for sampling stochastic tree ensembles using two algorithms: MCMC and Grow-From-Root (GFR)
• High-level model types supported:
  • Supervised learning with constant leaves or user-specified leaf regression models
  • Causal effect estimation with binary or continuous treatments
• Additional high-level modeling features:
  • Forest-based variance function estimation (heteroskedasticity)
  • Additive (univariate or multivariate) group random effects
  • Multi-chain sampling and support for parallelism
  • "Warm-start" initialization of MCMC forest samplers via the Grow-From-Root (GFR) algorithm
  • Automated preprocessing / handling of categorical variables
• Low-level interface:
  • Ability to combine a forest sampler with other (additive) model terms, without using C++
  • Combine and sample an arbitrary number of forests or random effects terms

stochtree documentation built on April 4, 2025, 2:11 a.m.