FarmTest

Factor Adjusted Robust Multiple Testing

Performs robust multiple testing for means in the presence of known and unknown latent factors. It implements a series of adaptive Huber methods combined with fast data-drive tuning schemes to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymetric error distributions. Extensions to two-sample simultaneous mean comparison problems are also included. As by-products, this package also contains functions that compute adaptive Huber mean and covariance matrix estimators that are of independent interest.

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Description file content

Package
FarmTest
Type
Package
Title
Factor Adjusted Robust Multiple Testing
Version
2.0.0
Date
2020-01-08
Author
Xiaoou Pan, Yuan Ke and Wen-Xin Zhou
Maintainer
Xiaoou Pan
Description
Performs robust multiple testing for means in the presence of known and unknown latent factors. It implements a series of adaptive Huber methods combined with fast data-drive tuning schemes to estimate model parameters and construct test statistics that are robust against heavy-tailed and/or asymetric error distributions. Extensions to two-sample simultaneous mean comparison problems are also included. As by-products, this package also contains functions that compute adaptive Huber mean and covariance matrix estimators that are of independent interest.
Depends
R (>= 3.6.0)
License
GPL-3
Encoding
UTF-8
URL
SystemRequirements
C++11
Imports
Rcpp
LinkingTo
Rcpp, RcppArmadillo
RoxygenNote
6.1.1
NeedsCompilation
yes
Packaged
2020-01-08 17:44:47 UTC; apple
Repository
CRAN
Date/Publication
2020-01-13 19:20:14 UTC

install.packages('FarmTest')

2.0.0

11 days ago

https://github.com/XiaoouPan/FarmTest

Xiaoou Pan

GPL-3

Depends on

R (>= 3.6.0)

Imports

Rcpp

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