FarmTest: Factor-Adjusted Robust Multiple Testing

Performs robust multiple testing for means in the presence of known and unknown latent factors presented in Fan et al.(2019) "FarmTest: Factor-Adjusted Robust Multiple Testing With Approximate False Discovery Control" <doi:10.1080/01621459.2018.1527700>. Implements a series of adaptive Huber methods combined with fast data-drive tuning schemes proposed in Ke et al.(2019) "User-Friendly Covariance Estimation for Heavy-Tailed Distributions" <doi:10.1214/19-STS711> to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymmetric error distributions. Extensions to two-sample simultaneous mean comparison problems are also included. As by-products, this package contains functions that compute adaptive Huber mean, covariance and regression estimators that are of independent interest.

Version:	2.2.0
Depends:	R (≥ 3.6.0)
Imports:	Rcpp, graphics
LinkingTo:	Rcpp, RcppArmadillo
Published:	2020-09-07
Author:	Xiaoou Pan [aut, cre], Yuan Ke [aut], Wen-Xin Zhou [aut]
Maintainer:	Xiaoou Pan <xip024 at ucsd.edu>
License:	GPL-3
URL:	https://github.com/XiaoouPan/FarmTest
NeedsCompilation:	yes
SystemRequirements:	C++11
Materials:	README
CRAN checks:	FarmTest results

Documentation:

Reference manual:

FarmTest.pdf

Downloads:

Package source:	FarmTest_2.2.0.tar.gz
Windows binaries:	r-devel: FarmTest_2.2.0.zip, r-release: FarmTest_2.2.0.zip, r-oldrel: FarmTest_2.2.0.zip
macOS binaries:	r-release (arm64): FarmTest_2.2.0.tgz, r-oldrel (arm64): FarmTest_2.2.0.tgz, r-release (x86_64): FarmTest_2.2.0.tgz, r-oldrel (x86_64): FarmTest_2.2.0.tgz
Old sources:	FarmTest archive

Linking:

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