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singR
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", "0.1.2")
Attach the package and use:
library("singR")
Maintained by
Liangkang Wang
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
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 0.1.2, https://cran.r-project.org/web/packages/singR. Accessed 04 Jan. 2025.
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Other R packages that singR depends,
imports, suggests or enhances
Complete documentation for singR
Functions, R codes and Examples using
the singR R package
Some associated functions: NG_number . angleMatchICA . aveM . calculateJB . covwhitener . create.graph.long . curvilinear . curvilinear_c . est.M.ols . exampledata . gen.inits . grapes-pow-grapes . greedymatch . lngca . matchICA . orthogonalize . permTestJointRank . permmatRank_joint . pmse . signchange . singR . standard . theta2W . tiltedgaussian . vec2net . whitener .
Some associated R codes: Match&Permutation_Functions.R . RcppExports.R . UpdateFunctions.R . dataset.R . graph.R . jngcaFunctions.R . lngca.R . singR.R . Full singR package functions and examples
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