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: | 2.1.0 |
| Depends: | R (≥ 3.6.0) |
| Imports: | Rcpp, graphics |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2020-04-28 |
| 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 |
| Reference manual: | FarmTest.pdf |
| Package source: | FarmTest_2.1.0.tar.gz |
| Windows binaries: | r-devel: FarmTest_2.1.0.zip, r-release: FarmTest_2.1.0.zip, r-oldrel: FarmTest_2.1.0.zip |
| macOS binaries: | r-release: FarmTest_2.1.0.tgz, r-oldrel: FarmTest_2.1.0.tgz |
| Old sources: | FarmTest archive |
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