ShrinkageTrees is an R package implementing regularized Bayesian tree ensembles for survival outcomes and causal inference via AFT models, including the first Horseshoe Forest implementation.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3verdicts
UNVERDICTED 3representative citing papers
A bilevel optimization framework smooths isotonic regression outputs into continuous piece-wise linear monotonic functions to recover marginal properties in both convex and non-convex cases.
Compares six meta-learners (Cox/RSF risk models paired with elastic net/RF CATE models) via simulations differing in hazard complexity and censoring, and releases the R package crsurvlearners.
citing papers explorer
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ShrinkageTrees: An R Package for Bayesian Tree Ensembles for Survival Analysis and Causal Inference
ShrinkageTrees is an R package implementing regularized Bayesian tree ensembles for survival outcomes and causal inference via AFT models, including the first Horseshoe Forest implementation.
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Piece-wise linear isotonic regression
A bilevel optimization framework smooths isotonic regression outputs into continuous piece-wise linear monotonic functions to recover marginal properties in both convex and non-convex cases.