Package: FarmTest 2.2.0

Xiaoou Pan

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.

Authors:Xiaoou Pan [aut, cre], Yuan Ke [aut], Wen-Xin Zhou [aut]

FarmTest_2.2.0.tar.gz
FarmTest_2.2.0.tar.gz(r-4.5-noble)FarmTest_2.2.0.tar.gz(r-4.4-noble)
FarmTest_2.2.0.tgz(r-4.4-emscripten)FarmTest_2.2.0.tgz(r-4.3-emscripten)
FarmTest.pdf |FarmTest.html✨
FarmTest/json (API)

# Install 'FarmTest' in R:
install.packages('FarmTest', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/xiaooupan/farmtest/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
  • openmp– GCC OpenMP (GOMP) support library

1.88 score 15 scripts 260 downloads 4 exports 2 dependencies

Last updated 4 years agofrom:97f447680a. Checks:OK: 1 NOTE: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 11 2024
R-4.5-linux-x86_64NOTENov 11 2024

Exports:farm.testhuber.covhuber.meanhuber.reg

Dependencies:RcppRcppArmadillo