Changes in version 1.0.1 (2026-08-09)                  

  - Internal cleanup of the C++ layer for CRAN portability: removed
    unused standard-library includes, routed all console output
    explicitly through Rcpp::Rcout, and restricted the shared library's
    symbol visibility to the registered entry points.

                        Changes in version 1.0.0                        

First release of FusionForests.

New model: FusionForest()

FusionForest() is a Bayesian tree ensemble for combining data from a
randomised controlled trial (RCT) and real-world data (RWD).

The outcome (continuous, or log survival time) is decomposed over
separate tree forests: a control forest, a treatment forest, a
deconfounding forest and a deviation forest that captures how the
treatment effect in the RWD deviates from the RCT. The observational
data are not assumed to be unconfounded.

Continuous, right-censored and interval-censored outcomes are supported
via an accelerated failure time formulation, with Gaussian or
Dirichlet-process mixture error distributions (error_dist).

Posterior summaries

  - fusion_estimand() — posterior draws of causal survival estimands:
    survival difference and acceleration factor.
  - fusion_projection() — interpretable linear projections of the
    posterior treatment effect surface.
  - print() and summary() methods for FusionForest fits.

Additional models

  - SimpleBART() — single-forest BART.
  - SimpleBCF() — Bayesian causal forest with prognostic and treatment
    forests.

Re-exports

The single-study causal and survival models from the ShrinkageTrees
package (ShrinkageTrees(), HorseTrees(), CausalShrinkageForest(),
CausalHorseForest(), SurvivalBART(), SurvivalDART(), SurvivalBCF(),
SurvivalShrinkageBCF()) are re-exported, so library(FusionForests)
provides every model from the accompanying paper in one namespace.