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singR  

Simultaneous Non-Gaussian Component Analysis
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("singR", "0.1.3")



Attach the package and use:
library("singR")
Maintained by
Liangkang Wang
[Scholar Profile | Author Map]
First Published: 2022-08-22
Latest Update: 2024-02-09
Description:
Implementation of SING algorithm to extract joint and individual non-Gaussian components from two datasets. SING uses an objective function that maximizes the skewness and kurtosis of latent components with a penalty to enhance the similarity between subject scores. Unlike other existing methods, SING does not use PCA for dimension reduction, but rather uses non-Gaussianity, which can improve feature extraction. Benjamin B.Risk, Irina Gaynanova (2021) <doi:10.1214/21-AOAS1466>.
How to cite:
Liangkang Wang (2022). singR: Simultaneous Non-Gaussian Component Analysis. R package version 0.1.3, https://cran.r-project.org/web/packages/singR. Accessed 29 Mar. 2025.
Previous versions and publish date:
0.1.0 (2022-08-22 16:40), 0.1.1 (2022-09-12 08:40), 0.1.2 (2024-02-09 01:20)
Other packages that cited singR R package
View singR citation profile
Other R packages that singR depends, imports, suggests or enhances
Complete documentation for singR
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