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LINselect  

Selection of Linear Estimators
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]
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 05 May. 2025.
Previous versions and publish date:
0.0-1 (2013-12-20 14:59), 0.0-2 (2015-08-26 22:59), 1.1.1 (2019-04-26 15:20), 1.1.2 (2020-01-09 19:30), 1.1.3 (2020-01-10 06:30), 1.1.4 (2023-08-30 10:10), 1.1 (2017-04-20 17:21)
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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