Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation.

@article{delosCampos2009ReproducingKH,
  title={Reproducing kernel Hilbert spaces regression: a general framework for genetic evaluation.},
  author={Gustavo de los Campos and Daniel Gianola and Guilherme J. M. Rosa},
  journal={Journal of animal science},
  year={2009},
  volume={87 6},
  pages={
          1883-7
        }
}
Reproducing kernel Hilbert spaces (RKHS) methods are widely used for statistical learning in many areas of endeavor. Recently, these methods have been suggested as a way of incorporating dense markers into genetic models. This note argues that RKHS regression provides a general framework for genetic evaluation that can be used either for pedigree- or marker-based regressions and under any genetic model, infinitesimal or not, and additive or not. Most of the standard models for genetic… 
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