Genome‐based prediction of Bayesian linear and non‐linear regression models for ordinal data

Abstract Linear and non‐linear models used in applications of genomic selection (GS) can fit different types of responses (e.g., continuous, ordinal, binary). In recent years, several genomic‐enabled prediction models have been developed for predicting complex traits in genomic‐assisted animal and p...

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Bibliographic Details
Main Authors: Paulino Pérez‐Rodríguez, Samuel Flores‐Galarza, Humberto Vaquera‐Huerta, David Hebert del Valle‐Paniagua, Osval A. Montesinos‐López, José Crossa
Format: Article
Language:English
Published: Wiley 2020-07-01
Series:The Plant Genome
Online Access:https://doi.org/10.1002/tpg2.20021