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Implementation of adaptive p-value thresholding (AdaPT), including both a framework that allows the user to specify any algorithm to learn local false discovery rate and a pool of convenient functions that implement specific algorithms. See Lei, Lihua and Fithian, William (2016) <doi:10.48550/arXiv.1609.06035>.
Version: | 1.0.0 |
Imports: | methods |
Suggests: | glmnet, HDtweedie, mgcv, splines, testthat, knitr, rmarkdown, dplyr |
Published: | 2018-07-31 |
DOI: | 10.32614/CRAN.package.adaptMT |
Author: | Lihua Lei [aut, cre] |
Maintainer: | Lihua Lei <lihua.lei at berkeley.edu> |
BugReports: | https://github.com/lihualei71/adaptMT/issues |
License: | MIT + file LICENSE |
URL: | https://arxiv.org/abs/1609.06035, https://github.com/lihualei71/adaptMT |
NeedsCompilation: | no |
Citation: | adaptMT citation info |
Materials: | README NEWS |
CRAN checks: | adaptMT results |
Reference manual: | adaptMT.pdf |
Vignettes: |
Introduction to 'adaptMT' package |
Package source: | adaptMT_1.0.0.tar.gz |
Windows binaries: | r-devel: adaptMT_1.0.0.zip, r-release: adaptMT_1.0.0.zip, r-oldrel: adaptMT_1.0.0.zip |
macOS binaries: | r-release (arm64): adaptMT_1.0.0.tgz, r-oldrel (arm64): adaptMT_1.0.0.tgz, r-release (x86_64): adaptMT_1.0.0.tgz, r-oldrel (x86_64): adaptMT_1.0.0.tgz |
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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.