Package: predhy 2.1.1

predhy: Genomic Prediction of Hybrid Performance

Performs genomic prediction of hybrid performance using eight GS methods including GBLUP, BayesB, RKHS, PLS, LASSO, Elastic net, LightGBM 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>).

Authors:Yang Xu, Guangning Yu, Yanru Cui, Shizhong Xu, Chenwu Xu

predhy_2.1.1.tar.gz
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predhy.pdf |predhy.html
predhy/json (API)

# Install 'predhy' in R:
install.packages('predhy', repos = c('https://yangxu89.r-universe.dev', 'https://cloud.r-project.org'))
Datasets:

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

1.78 score 1 stars 1 packages 257 downloads 9 exports 20 dependencies

Last updated 10 months agofrom:6e53c6359f. Checks:9 OK. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 20 2025
R-4.5-winOKMar 20 2025
R-4.5-macOKMar 20 2025
R-4.5-linuxOKMar 20 2025
R-4.4-winOKMar 20 2025
R-4.4-macOKMar 20 2025
R-4.4-linuxOKMar 20 2025
R-4.3-winOKMar 20 2025
R-4.3-macOKMar 20 2025

Exports:convertgencrodesigncvcv_fastinfergenkinmixedpredhy.predictpredhy.predict_NCII

Dependencies:BGLRcodetoolsdata.tabledoParallelforeachglmnetiteratorsjsonlitelatticelightgbmMASSMatrixplsR6RcppRcppEigenshapesurvivaltruncnormxgboost