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# CITATION.cff file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "KRMM" in publications use:'
type: software
license:
- GPL-2.0-only
- GPL-3.0-only
title: 'KRMM: Kernel Ridge Mixed Model'
version: '1.0'
doi: 10.32614/CRAN.package.KRMM
abstract: 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. <https://doi.org/10.3389/fgene.2016.00145>.
authors:
- family-names: Jacquin
  given-names: Laval
  email: jacquin.julien@gmail.com
repository: https://cranhaven.r-universe.dev
commit: 8b462d9a0b8cec6759a2b97a108a05d6ddf6738b
date-released: '2026-10-12'
contact:
- family-names: Jacquin
  given-names: Laval
  email: jacquin.julien@gmail.com