SplitKnockoff: Split Knockoffs for Structural Sparsity

A novel method for controlling the false discovery rate (FDR) in structural sparsity setting. This proposed scheme relaxes the linear subspace constraint to its neighborhood, often known as variable splitting in optimization. Simulation experiments can be reproduced following the Vignette. We include data (both .mat and .csv format) and application with our method of Alzheimer’s Disease study in this package. 'Split Knockoffs' is defined in Cao et al. (2021) <arXiv:2103.16159>.

Version: 1.0
Depends: R (≥ 3.5.0)
Imports: glmnet, MASS, latex2exp, RSpectra, ggplot2, Matrix, stats, mvtnorm
Suggests: knitr, rmarkdown
Published: 2021-11-02
Author: Haoxue Wang [aut, cre] (Development of the whole packages), Yang Cao [aut] (Revison of this package), Xinwei Sun [aut] (Original ideas about the package), Yuan Yao [aut] (Testing for the package and management of the development)
Maintainer: Haoxue Wang <haoxwang at student.ethz.ch>
BugReports: https://github.com/wanghaoxue0/SplitKnockoff/issues
License: MIT + file LICENSE
URL: https://github.com/wanghaoxue0/SplitKnockoff
NeedsCompilation: no
CRAN checks: SplitKnockoff results


Reference manual: SplitKnockoff.pdf
Vignettes: Splitknockoff


Package source: SplitKnockoff_1.0.tar.gz
Windows binaries: r-devel: SplitKnockoff_1.0.zip, r-release: SplitKnockoff_1.0.zip, r-oldrel: SplitKnockoff_1.0.zip
macOS binaries: r-release (arm64): SplitKnockoff_1.0.tgz, r-release (x86_64): SplitKnockoff_1.0.tgz, r-oldrel: SplitKnockoff_1.0.tgz
Old sources: SplitKnockoff archive


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