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KSA  

Retained Component Criterion for Principal Component Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("KSA", "0.1.0")



Attach the package and use:
library("KSA")
Maintained by
Dr. Fayed Alshammri
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-09-21
Latest Update: 2022-09-21
Description:
The Retained Component Criterion for Principal Component Analysis (RCC_PCA) is a tool to determine the optimal number of components to retain in PCA.
How to cite:
Dr. Fayed Alshammri (2022). KSA: Retained Component Criterion for Principal Component Analysis. R package version 0.1.0, https://cran.r-project.org/web/packages/KSA. Accessed 05 Oct. 2026.
Previous versions and publish date:
No previous versions
Other packages that cited KSA R package
View KSA citation profile
Other R packages that KSA depends, imports, suggests or enhances
Complete documentation for KSA
Functions, R codes and Examples using the KSA R package
Some associated functions: RCC_PCA . 
Some associated R codes: RCC_PCA.R .  Full KSA package functions and examples
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