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 |
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