Package: ShrinkageTrees 2.0.2

Introduction | Package map | Key Concepts | Outcome types and the timescale parameter | Shrinkage priors on the step heights | Hyperparameter selection | The store_posterior_sample flag | Treatment coding (treatment_coding) | Included Datasets | The PDAC Dataset | Prediction Models | HorseTrees — binary outcome (propensity scores) | HorseTrees — survival outcome | HorseTrees — interval-censored outcome | ShrinkageTrees — flexible prior choice | SurvivalBART and SurvivalDART | High-Dimensional Survival Analysis | Causal Forest Models | SurvivalBCF — classical BCF for survival | SurvivalShrinkageBCF — sparse causal survival forest | CausalHorseForest — horseshoe causal forest | CausalShrinkageForest — flexible causal priors | S3 Methods | print() | summary() | Population vs. mixed ATE | predict() | Causal predictions | plot() | Sigma traceplot | Posterior ATE distribution (causal models) | CATE caterpillar plot | Variable importance (Dirichlet prior) | Survival curves | Posterior predictive survival curves | Multi-Chain MCMC | Convergence Diagnostics | Acceptance ratio | Formal diagnostics with coda | Recommended MCMC settings | Case Study: TCGA PAAD (Full Analysis) | Step 1: Propensity score estimation | Step 2: Causal survival forest | Step 3: ATE and CATE estimation | Step 4: Diagnostics | References