Now showing items 1-4 of 4
A bayesian poisson-lognormal model for count data for multiple-trait multiple-environment genomic-enabled prediction
(Genetics Society of America, 2017)
When a plant scientist wishes to make genomic-enabled predictions of multiple traits measured in multiple individuals in multiple environments, the most common strategy for performing the analysis is to use a single trait ...
A multivariate Poisson deep learning model for genomic prediction of count data
(Genetics Society of America, 2020)
A zero altered Poisson random forest model for genomic-enabled prediction
(Genetics Society of America, 2021)
Prediction of multiple-trait and multiple-environment genomic data using recommender systems
(Genetics Society of America, 2018)
In genomic-enabled prediction, the task of improving the accuracy of the prediction of lines in environments is difficult because the available information is generally sparse and usually has low correlations between traits. ...