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 http://www.hsph.harvard.edu/xlin/software.html.

AuthorRachel Marceau, Wenbin Lu, Michele M. Sale, Bradford B. Worrall, Stephen R. Williams, Fang-Chi Hsu, Jung-Ying Tzeng, and Shannon T. Holloway
Date of publication2015-11-10 11:08:14
MaintainerShannon T. Holloway <sthollow@ncsu.edu>
LicenseGPL-2
Version1.0

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