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>.


Reference manual

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install.packages("FastKM")

1.2 by Shannon T. Holloway, a year ago


Browse source code at https://github.com/cran/FastKM


Authors: 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]


Documentation:   PDF Manual  


GPL-2 license


Depends on rARPACK, stats, methods

Suggests coxKM, SKAT, survival


See at CRAN