A Fast Multiple-Kernel Method Based on a Low-Rank Approximation
Overview
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.
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- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK12 OK2026-04-25
- NOTE11 OK, 3 NOTE2026-03-10
Documentation
- Help pages
- 7includes a package overview page
- Examples that run
- 100%6 run in a plain check (2 of them under a condition)
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 43%
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- RR 4.6.0 released · 2026-04-24
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- RR 4.5.0 released · 2025-04-11
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- RR 4.3.0 released · 2023-04-21
- 1.12022-06-07 · diff ↗
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- RR 4.0.0 released · 2020-04-24
- RR 3.6.0 released · 2019-04-26
- RR 3.5.0 released · 2018-04-23
- RR 3.4.0 released · 2017-04-21
- RR 3.3.0 released · 2016-05-03
- 1.02015-11-10
- RR 3.2.0 released · 2015-04-16
Package metadata
- First published
- 2015-11-10
- Total releases
- 3 / 11 yrs
- License
- GPL-2 OSI
- Download size
- 16 KB
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