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TPLSr  

Thresholded Partial Least Squares Model for Neuroimaging Data
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("TPLSr", "1.0.5")



Attach the package and use:
library("TPLSr")
Maintained by
Sangil Lee
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-11-02
Latest Update: 2022-06-10
Description:
Uses thresholded partial least squares algorithm to create a regression or classification model. For more information, see Lee, Bradlow, and Kable <doi:10.1016/j.crmeth.2022.100227>.
How to cite:
Sangil Lee (2020). TPLSr: Thresholded Partial Least Squares Model for Neuroimaging Data. R package version 1.0.5, https://cran.r-project.org/web/packages/TPLSr. Accessed 07 Oct. 2026.
Previous versions and publish date:
(2026-07-09 08:27), 1.0.1 (2020-11-02 18:10), 1.0.3 (2021-04-08 23:40), 1.0.4 (2022-06-10 23:20)
Other packages that cited TPLSr R package
View TPLSr citation profile
Other R packages that TPLSr depends, imports, suggests or enhances
Complete documentation for TPLSr
Functions, R codes and Examples using the TPLSr R package
Some associated functions: TPLS . TPLS_cv . TPLSdat . TPLSpredict . evalTuningParam . makePredictor . plotTuningSurface . 
Some associated R codes: TPLS.R . TPLS_cv.R . TPLSinputchecker.R . data.R . evalTuningParam.R .  Full TPLSr package functions and examples
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