FusionForests 1.0.1

• 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.

FusionForests 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.