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Estimating heterogeneous treatment effects with tree-based machine learning algorithms and visualizing estimated results in flexible and presentation-ready ways. For more information, see Brand, Xu, Koch, and Geraldo (2021) <doi:10.1177/0081175021993503>. Our current package first started as a fork of the 'causalTree' package on 'GitHub' and we greatly appreciate the authors for their extremely useful and free package.
| Version: | 0.1.18 |
| Depends: | R (≥ 3.6.0) |
| Imports: | Rcpp, grf, partykit, data.tree, Matching, dplyr, jsonlite, rpart, rpart.plot, shiny, stringr |
| Suggests: | optmatch, haven, foreign, data.table, remotes, party |
| Published: | 2023-11-29 |
| Author: | Jiahui Xu [cre, aut], Tanvi Shinkre [aut], Jennie Brand [aut] |
| Maintainer: | Jiahui Xu <jiahuixu at ucla.edu> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | yes |
| CRAN checks: | htetree results |
| Reference manual: | htetree.pdf |
| Package source: | htetree_0.1.18.tar.gz |
| Windows binaries: | r-devel: htetree_0.1.18.zip, r-release: htetree_0.1.18.zip, r-oldrel: htetree_0.1.18.zip |
| macOS binaries: | r-release (arm64): htetree_0.1.18.tgz, r-oldrel (arm64): htetree_0.1.18.tgz, r-release (x86_64): htetree_0.1.18.tgz, r-oldrel (x86_64): htetree_0.1.18.tgz |
| Old sources: | htetree archive |
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These binaries (installable software) and packages are in development.
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