aggTrees: Aggregation Trees

Nonparametric data-driven approach to discovering heterogeneous subgroups in a selection-on-observables framework. aggTrees allows researchers to assess whether there exists relevant heterogeneity in treatment effects by generating a sequence of optimal groupings, one for each level of granularity. For each grouping, we obtain point estimation and inference about the Group Average Treatment Effects. Please reference the use as Di Francesco (2022) <doi:10.2139/ssrn.4304256>.

Version: 2.0.2
Depends: R (≥ 2.10)
Imports: boot, broom, car, caret, estimatr, grf, rpart, rpart.plot, stats, stringr
Suggests: knitr, rmarkdown
Published: 2023-09-20
DOI: 10.32614/CRAN.package.aggTrees
Author: Riccardo Di Francesco [aut, cre, cph]
Maintainer: Riccardo Di Francesco <difrancesco.riccardo96 at>
License: MIT + file LICENSE
NeedsCompilation: no
Materials: README NEWS
CRAN checks: aggTrees results


Reference manual: aggTrees.pdf
Vignettes: Short Tutorial


Package source: aggTrees_2.0.2.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): aggTrees_2.0.2.tgz, r-oldrel (arm64): aggTrees_2.0.2.tgz, r-release (x86_64): aggTrees_2.0.2.tgz, r-oldrel (x86_64): aggTrees_2.0.2.tgz
Old sources: aggTrees archive


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