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SFSI  

Sparse Family and Selection Index
View on CRAN: Click here


Download and install SFSI package within the R console
Install from CRAN:
install.packages("SFSI")

Install from Github:
library("remotes")
install_github("cran/SFSI")

Install by package version:
library("remotes")
install_version("SFSI", "1.4.1")



Attach the package and use:
library("SFSI")
Maintained by
Marco Lopez-Cruz
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2021-05-03
Latest Update: 2024-01-12
Description:
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') .
How to cite:
Marco Lopez-Cruz (2021). SFSI: Sparse Family and Selection Index. R package version 1.4.1, https://cran.r-project.org/web/packages/SFSI. Accessed 02 Feb. 2025.
Previous versions and publish date:
0.3.0 (2021-05-03 09:50), 0.4.0 (2021-05-16 00:00), 1.0.0 (2021-09-30 19:50), 1.0.1 (2022-01-27 00:30), 1.1.0 (2022-03-10 22:30), 1.2.0 (2022-08-16 17:40), 1.3.1 (2023-11-18 08:00), 1.4 (2024-06-25 16:50)
Other packages that cited SFSI R package
View SFSI citation profile
Other R packages that SFSI depends, imports, suggests or enhances
Complete documentation for SFSI
Functions, R codes and Examples using the SFSI R package
Some associated functions: BinaryFiles . LARS . Methods_LASSO . Methods_SSI . SSI . collect . covariance_matrix . fitBLUP . getGenCov . net.plot . path.plot . solveEN . wheat . 
Some associated R codes: LARS.R . Prune.R . SSI.CV.R . SSI.R . collect.R . cov2cor.R . cov2dist.R . fitBLUP.R . getGenCov.R . methods.R . net.plot.R . path.plot.R . readBinary.R . rrr_functions.R . saveBinary.R . solveEN.R .  Full SFSI package functions and examples
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