krm: Kernel Based Regression Models

Implements several methods for testing the variance component parameter in regression models that contain kernel-based random effects, including a maximum of adjusted scores test. Several kernels are supported, including a profile hidden Markov model mutual information kernel for protein sequence. This package is described in Fong et al. (2015) <doi:10.1093/biostatistics/kxu056>.

Version: 2022.10-17
Depends: R (≥ 3.3.0), kyotil
Imports: methods
Suggests: RUnit, MASS
Published: 2022-10-18
DOI: 10.32614/CRAN.package.krm
Author: Youyi Fong [cre], Saheli Datta [aut], Krisztian Sebestyen [aut], Steve Park [ctb], Dave Geyer [ctb]
Maintainer: Youyi Fong <youyifong at gmail.com>
License: GPL-2
NeedsCompilation: yes
Materials: ChangeLog
In views: Omics
CRAN checks: krm results

Documentation:

Reference manual: krm.pdf

Downloads:

Package source: krm_2022.10-17.tar.gz
Windows binaries: r-devel: krm_2022.10-17.zip, r-release: krm_2022.10-17.zip, r-oldrel: krm_2022.10-17.zip
macOS binaries: r-release (arm64): krm_2022.10-17.tgz, r-oldrel (arm64): krm_2022.10-17.tgz, r-release (x86_64): krm_2022.10-17.tgz, r-oldrel (x86_64): krm_2022.10-17.tgz
Old sources: krm archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=krm to link to this page.