FastKM: A fast multiple-kernel method based on a low-rank approximation (R).

TitleFastKM: A fast multiple-kernel method based on a low-rank approximation (R).
Publication TypeSoftware
Year of Publication2015
AuthorsMarceau, Rachel, Wenbin Lu, Michèle M. Sale, Bradford B. Worrall, Stephen R. Williams, Fang-Chi Hsu, Jung-Ying Tzeng, and Shannon T. Holloway
Version1.0
Abstract

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.
Original PublicationFastKM: A fast multiple-kernel method based on a low-rank approximation (R).
Project: 
Project 2.3
Software Demonstration Weblink: 
FastKM: R package