Efficient implementations of the algorithms in the Almost-Matching-Exactly framework for interpretable matching in causal inference. These algorithms match units via a learned, weighted Hamming distance that determines which covariates are more important to match on. For more information and examples, see the Almost-Matching-Exactly website.
Version: | 2.0.0 |
Imports: | dplyr, magrittr, mice, glmnet, gmp, rlang, tidyr, xgboost, devtools |
Suggests: | testthat, knitr, rmarkdown |
Published: | 2020-04-15 |
Author: | Vittorio Orlandi [aut, cre], Sudeepa Roy [aut], Cynthia Rudin [aut], Alexander Volfovsky [aut] |
Maintainer: | Vittorio Orlandi <almost.matching.exactly at gmail.com> |
BugReports: | https://github.com/vittorioorlandi/FLAME/issues |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
CRAN checks: | FLAME results |
Reference manual: | FLAME.pdf |
Vignettes: |
Introduction to FLAME |
Package source: | FLAME_2.0.0.tar.gz |
Windows binaries: | r-devel: FLAME_2.0.0.zip, r-release: FLAME_2.0.0.zip, r-oldrel: FLAME_2.0.0.zip |
macOS binaries: | r-release: FLAME_2.0.0.tgz, r-oldrel: FLAME_2.0.0.tgz |
Old sources: | FLAME archive |
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