Package: KRMM
Type: Package
Title: Kernel Ridge Mixed Model
Version: 1.1
Authors@R: person("Laval", "Jacquin", email = "jacquin.julien@gmail.com", role = c("aut", "cre"))
Author: Laval Jacquin [aut, cre]
Maintainer: Laval Jacquin <jacquin.julien@gmail.com>
Description: 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>.
Depends: R (>= 3.3.0)
Imports:
        stats,MASS,kernlab,cvTools,robustbase,foreach,parallel,doParallel,Matrix
License: GPL-2 | GPL-3
Encoding: UTF-8
RoxygenNote: 5.0.1
NeedsCompilation: no
Re-packaged: 2024-04-14 10:00:00 UTC; laval_jacquin
Repository: https://ljacquin.r-universe.dev
Date/Publication: 2024-11-27 09:41:26 UTC
RemoteUrl: https://github.com/ljacquin/krmm
RemoteRef: HEAD
RemoteSha: cb010a23da2d4eb854d43186bb76208f69137622
Packaged: 2026-09-21 11:40:57 UTC; root