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FastKM: A Fast Multiple-Kernel Method Based on a Low-Rank Approximation

A computationally efficient and statistically rigorous fast Kernel Machine method for multi-kernel analysis. The approach is based on a low-rank approximation to the nuisance effect kernel matrices. The algorithm is applicable to continuous, binary, and survival traits and is implemented using the existing single-kernel analysis software 'SKAT' and 'coxKM'. 'coxKM' can be obtained from <https://github.com/lin-lab/coxKM>.

Version:1.2
Depends:rARPACK, stats, methods
Suggests:coxKM,SKAT,survival
Published:2025-05-04
DOI:10.32614/CRAN.package.FastKM
Author:Rachel Marceau [aut], Wenbin Lu [aut], Michele M. Sale [aut], Bradford B. Worrall [aut], Stephen R. Williams [aut], Fang-Chi Hsu [aut], Jung-Ying Tzeng [aut], Shannon T. Holloway [aut, cre]
Maintainer:Shannon T. Holloway <shannon.t.holloway at gmail.com>
License:GPL-2
NeedsCompilation:no
Materials:NEWS
CRAN checks:FastKM results

Documentation:

Reference manual:FastKM.html ,FastKM.pdf

Downloads:

Package source: FastKM_1.2.tar.gz
Windows binaries: r-devel:FastKM_1.2.zip, r-release:FastKM_1.2.zip, r-oldrel:FastKM_1.2.zip
macOS binaries: r-release (arm64):FastKM_1.2.tgz, r-oldrel (arm64):FastKM_1.2.tgz, r-release (x86_64):FastKM_1.2.tgz, r-oldrel (x86_64):FastKM_1.2.tgz
Old sources: FastKM archive

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=FastKMto link to this page.


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