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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: | 2.1.1 |
Imports: | glmnet, gmp |
Suggests: | nnet, knitr, mice, rmarkdown, testthat, xgboost |
Published: | 2021-12-07 |
DOI: | 10.32614/CRAN.package.FLAME |
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 |
URL: | https://almost-matching-exactly.github.io,https://vittorioorlandi.github.io/ |
NeedsCompilation: | no |
In views: | CausalInference |
CRAN checks: | FLAME results |
Reference manual: | FLAME.pdf |
Vignettes: |
intro_to_AME |
Package source: | FLAME_2.1.1.tar.gz |
Windows binaries: | r-devel: FLAME_2.1.1.zip, r-release: FLAME_2.1.1.zip, r-oldrel: FLAME_2.1.1.zip |
macOS binaries: | r-release (arm64): FLAME_2.1.1.tgz, r-oldrel (arm64): FLAME_2.1.1.tgz, r-release (x86_64): FLAME_2.1.1.tgz, r-oldrel (x86_64): FLAME_2.1.1.tgz |
Old sources: | FLAME archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.