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clr  

Curve Linear Regression via Dimension Reduction
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("clr", "0.1.2")



Attach the package and use:
library("clr")
Maintained by
Amandine Pierrot
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-12-03
Latest Update: 2019-07-29
Description:
A new methodology for linear regression with both curve response and curve regressors, which is described in Cho, Goude, Brossat and Yao (2013) and (2015) . The key idea behind this methodology is dimension reduction based on a singular value decomposition in a Hilbert space, which reduces the curve regression problem to several scalar linear regression problems.
How to cite:
Amandine Pierrot (2018). clr: Curve Linear Regression via Dimension Reduction. R package version 0.1.2, https://cran.r-project.org/web/packages/clr. Accessed 18 Sep. 2026.
Previous versions and publish date:
(2026-08-31 22:50), 0.1.0 (2018-12-03 13:12), 0.1.1 (2019-01-11 17:20), 0.1.2 (2019-07-29 11:00)
Other packages that cited clr R package
View clr citation profile
Other R packages that clr depends, imports, suggests or enhances
Complete documentation for clr
Functions, R codes and Examples using the clr R package
Some associated functions: clr-package . clr . clrdata . clust_test . clust_train . gb_load . predict.clr . 
Some associated R codes: clr-package.R . clr.R . clust_test-data.R . clust_train-data.R . gb_load-data.R . manage-data.R . predict-clr.R .  Full clr package functions and examples
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