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: 1.1
Depends: rARPACK, stats, methods
Suggests: coxKM, SKAT, survival
Published: 2022-06-07
Author: Rachel Marceau, Wenbin Lu, Michele M. Sale, Bradford B. Worrall, Stephen R. Williams, Fang-Chi Hsu, Jung-Ying Tzeng, and Shannon T. Holloway
Maintainer: Shannon T. Holloway <shannon.t.holloway at gmail.com>
License: GPL-2
NeedsCompilation: no
CRAN checks: FastKM results

Documentation:

Reference manual: FastKM.pdf

Downloads:

Package source: FastKM_1.1.tar.gz
Windows binaries: r-devel: FastKM_1.1.zip, r-release: FastKM_1.1.zip, r-oldrel: FastKM_1.1.zip
macOS binaries: r-release (arm64): FastKM_1.1.tgz, r-oldrel (arm64): FastKM_1.1.tgz, r-release (x86_64): FastKM_1.1.tgz, r-oldrel (x86_64): FastKM_1.1.tgz
Old sources: FastKM archive

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