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_2.1.1.tgz(r-4.4-any)predhy_2.1.1.tgz(r-4.3-any)
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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'))

Peer review:

Datasets:

On CRAN:

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

1.95 score 1 stars 1 packages 254 downloads 9 exports 20 dependencies

Last updated 6 months agofrom:6e53c6359f. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 20 2024
R-4.5-winOKNov 20 2024
R-4.5-linuxOKNov 20 2024
R-4.4-winOKNov 20 2024
R-4.4-macOKNov 20 2024
R-4.3-winOKNov 20 2024
R-4.3-macOKNov 20 2024

Exports:convertgencrodesigncvcv_fastinfergenkinmixedpredhy.predictpredhy.predict_NCII

Dependencies:BGLRcodetoolsdata.tabledoParallelforeachglmnetiteratorsjsonlitelatticelightgbmMASSMatrixplsR6RcppRcppEigenshapesurvivaltruncnormxgboost