Ontology highlight
ABSTRACT:
SUBMITTER: Perez-Rodriguez P
PROVIDER: S-EPMC3516481 | biostudies-literature | 2012 Dec
REPOSITORIES: biostudies-literature
Pérez-Rodríguez Paulino P Gianola Daniel D González-Camacho Juan Manuel JM Crossa José J Manès Yann Y Dreisigacker Susanne S
G3 (Bethesda, Md.) 20121201 12
In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural net ...[more]