The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.
Solves kernel ridge regression, within the the mixed model framework, for the linear, polynomial, Gaussian, Laplacian and ANOVA kernels. The model components (i.e. fixed and random effects) and variance parameters are estimated using the expectation-maximization (EM) algorithm. All the estimated components and parameters, e.g. BLUP of dual variables and BLUP of random predictor effects for the linear kernel (also known as RR-BLUP), are available. The kernel ridge mixed model (KRMM) is described in Jacquin L, Cao T-V and Ahmadi N (2016) A Unified and Comprehensible View of Parametric and Kernel Methods for Genomic Prediction with Application to Rice. Front. Genet. 7:145. <doi:10.3389/fgene.2016.00145>.
| Version: | 1.0 |
| Depends: | R (≥ 3.3.0) |
| Imports: | stats, MASS, kernlab, cvTools, robustbase |
| Published: | 2017-06-03 |
| DOI: | 10.32614/CRAN.package.KRMM |
| Author: | Laval Jacquin [aut, cre] |
| Maintainer: | Laval Jacquin <jacquin.julien at gmail.com> |
| License: | GPL-2 | GPL-3 |
| NeedsCompilation: | no |
| CRAN checks: | KRMM results |
| Reference manual: | KRMM.pdf |
| Package source: | KRMM_1.0.tar.gz |
| Windows binaries: | r-devel: KRMM_1.0.zip, r-release: KRMM_1.0.zip, r-oldrel: KRMM_1.0.zip |
| macOS binaries: | r-release (arm64): KRMM_1.0.tgz, r-oldrel (arm64): KRMM_1.0.tgz, r-release (x86_64): KRMM_1.0.tgz, r-oldrel (x86_64): KRMM_1.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=KRMM to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.