StochTree R API Reference

Overview of the stochtree R library's key classes and functions, built as a self-contained doc site using the pkgdown format. The stochtree interface is divided into two "levels":

1. "High level": end-to-end implementations of stochastic tree ensembles for supervised learning (BART / XBART) and causal inference (BCF / XBCF).
   1. The BART (supervised learning) interface is documented here.
   2. The BCF (causal inference) interface is documented here.
2. "Low level": we provide access to most of the C++ sampling objects and functionality via R, which allow for custom sampling algorithms and integration of other model terms. This interface consists broadly of the following components:
   1. Data API: loading and storing in-memory data needed to train stochtree models.
   2. Forest API: creating, storing, modifying, and sampling ensembles of decision trees that underlie all stochtree models.
   3. Serialization API: serializing models to JSON (files or in-memory strings).
   4. Random Effects API: sampling from additive random effects models.