CRAN/E | singR

singR

Simultaneous Non-Gaussian Component Analysis

Installation

About

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.

Citation singR citation info

Key Metrics

Version 0.1.2
R ≥ 2.10
Published 2024-02-09 241 days ago
Needs compilation? yes
License MIT
License File
CRAN checks singR results

Downloads

Yesterday 5 0%
Last 7 days 34 -43%
Last 30 days 2.017 -46%
Last 90 days 8.211 -55%
Last 365 days 73.621 +3231%

Maintainer

Maintainer

Liangkang Wang

Authors

Liangkang Wang

aut / cre

Irina Gaynanova

aut

Benjamin Risk

aut

Material

Reference manual
Package source

Vignettes

singR-tutorial

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

singR archive

Depends

R ≥ 2.10

Imports

MASS ≥ 7.3-57
Rcpp ≥ 1.0.8.3
clue ≥ 0.3-61
gam ≥1.20.1
ICtest ≥ 0.3-5

Suggests

knitr
covr
testthat ≥ 3.0.0
rmarkdown

LinkingTo

Rcpp
RcppArmadillo