Sparse Family and Selection Index

Here we provide tools for the estimation of coefficients in penalized regressions when the (co)variance matrix of predictors and the covariance vector between predictors and response, are provided. These methods are extended to the context of a Selection Index (commonly used for breeding value prediction). The approaches offer opportunities such as the integration of high-throughput traits in genetic evaluations ('Lopez-Cruz et al., 2020') and solutions for training set optimization in Genomic Prediction ('Lopez-Cruz & de los Campos, 2021') .


Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("SFSI")

1.4.1 by Marco Lopez-Cruz, 2 years ago


https://github.com/MarcooLopez/SFSI


Browse source code at https://github.com/cran/SFSI


Authors: Marco Lopez-Cruz [aut, cre] , Gustavo de los Campos [aut] , Paulino Perez-Rodriguez [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports stats, scales, tensorEVD, parallel, reshape2, viridis, igraph, stringr, ggplot2

Suggests BGLR, knitr, rmarkdown


See at CRAN