Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Whea...
Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat
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Publisher
United States: Oxford University Press
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Language
English
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Publisher
United States: Oxford University Press
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Abstract
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...
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Full title
Comparison Between Linear and Non-parametric Regression Models for Genome-Enabled Prediction in Wheat
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TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3516481
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_3516481
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ISSN
2160-1836
E-ISSN
2160-1836
DOI
10.1534/g3.112.003665
