predhy: Genomic Prediction of Hybrid Performance

Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, Random forest and XGBoost. It also provides fast cross-validation and mating design scheme for training population (Xu S et al (2016) <doi:10.1111/tpj.13242>; Xu S (2017) <doi:10.1534/g3.116.038059>).

Version: 1.2.0
Depends: R (≥ 3.6.0)
Imports: BGLR, pls, glmnet, randomForest, xgboost, foreach, doParallel, parallel
Published: 2021-08-16
Author: Yang Xu, Guangning Yu, Yanru Cui, Shizhong Xu, Chenwu Xu
Maintainer: Yang Xu <xuyang_89 at>
License: GPL-3
NeedsCompilation: no
CRAN checks: predhy results


Reference manual: predhy.pdf


Package source: predhy_1.2.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): predhy_1.2.0.tgz, r-release (x86_64): predhy_1.2.0.tgz, r-oldrel: predhy_1.2.0.tgz
Old sources: predhy archive


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