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springer
Sparse Group Variable Selection for Gene-Environment Interactions in the Longitudinal Study
View on CRAN: Click
here
Download and install springer package within the R console
Install from CRAN:
install.packages("springer")
Install from Github:
library("remotes")
install_github("cran/springer") Install by package version:
library("remotes")
install_version("springer", "0.1.9") Attach the package and use:
library("springer")
Maintained by
Fei Zhou
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-06-28
Latest Update: 2024-02-01
Description:
Recently, regularized variable selection has emerged as a powerful tool to identify and dissect gene-environment interactions. Nevertheless, in longitudinal studies with high dimensional genetic factors, regularization methods for G×E interactions have not been systematically developed. In this package, we provide the implementation of sparse group variable selection, based on both the quadratic inference function (QIF) and generalized estimating equation (GEE), to accommodate the bi-level selection for longitudinal G×E studies with high dimensional genomic features. Alternative methods conducting only the group or individual level selection have also been included. The core modules of the package have been developed in C++.
How to cite:
Fei Zhou (2020). springer: Sparse Group Variable Selection for Gene-Environment Interactions in the Longitudinal Study. R package version 0.1.9, https://cran.r-project.org/web/packages/springer. Accessed 18 Sep. 2026.
Previous versions and publish date:
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Complete documentation for springer
Functions, R codes and Examples using
the springer R package
Some associated functions: cv.springer . dat . dmcp . penalty . print.springer . reformat . springer-package . springer .
Some associated R codes: RcppExports.R . cv.springer.R . data.R . dmcp.R . penalty.R . print.springer.R . reformat.R . springer-package.R . springer.R . Full springer package functions and examples
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