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LINselect
View on CRAN: Click
here
Download and install LINselect package within the R console
Install from CRAN:
install.packages("LINselect")
Install from Github:
library("remotes")
install_github("cran/LINselect")
Install by package version:
library("remotes")
install_version("LINselect", "1.1.5")
Attach the package and use:
library("LINselect")
Maintained by
Benjamin Auder
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2013-12-20
Latest Update: 2023-08-30
Description:
Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators,
following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) .
In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso,
elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.
How to cite:
Benjamin Auder (2013). LINselect: Selection of Linear Estimators. R package version 1.1.5, https://cran.r-project.org/web/packages/LINselect. Accessed 21 Nov. 2024.
Previous versions and publish date:
Other packages that cited LINselect R package
View LINselect citation profile
Other R packages that LINselect depends,
imports, suggests or enhances
Complete documentation for LINselect
Functions, R codes and Examples using
the LINselect R package
Some associated functions: LINselect-package . VARselect . penalty . simulData . tuneLasso .
Some associated R codes: VARselect.R . functions.R . penalty.R . simulData.R . tuneLasso.R . Full LINselect package functions and examples
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