sdafilter: Symmetrized Data Aggregation

We develop a new class of distribution free multiple testing rules for false discovery rate (FDR) control under general dependence. A key element in our proposal is a symmetrized data aggregation (SDA) approach to incorporating the dependence structure via sample splitting, data screening and information pooling. The proposed SDA filter first constructs a sequence of ranking statistics that fulfill global symmetry properties, and then chooses a data driven threshold along the ranking to control the FDR. For more information, see the website below and the accompanying paper: Du et al. (2020), "False Discovery Rate Control Under General Dependence By Symmetrized Data Aggregation", <doi:10.48550/arXiv.2002.11992>.

Version: 1.0.0
Imports: glmnet, glasso, huge, POET, stats
Suggests: testthat (≥ 2.1.0)
Published: 2020-03-19
DOI: 10.32614/CRAN.package.sdafilter
Author: Lilun Du [aut, cre], Xu Guo [ctb], Wenguang Sun [ctb], Changliang Zou [ctb]
Maintainer: Lilun Du <dulilun at ust.hk>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
CRAN checks: sdafilter results

Documentation:

Reference manual: sdafilter.pdf

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Package source: sdafilter_1.0.0.tar.gz
Windows binaries: r-devel: sdafilter_1.0.0.zip, r-release: sdafilter_1.0.0.zip, r-oldrel: sdafilter_1.0.0.zip
macOS binaries: r-release (arm64): sdafilter_1.0.0.tgz, r-oldrel (arm64): sdafilter_1.0.0.tgz, r-release (x86_64): sdafilter_1.0.0.tgz, r-oldrel (x86_64): sdafilter_1.0.0.tgz

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