The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

singR: Simultaneous Non-Gaussian Component Analysis

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>.

Version: 0.1.2
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)
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, covr, testthat (≥ 3.0.0), rmarkdown
Published: 2024-02-09
DOI: 10.32614/CRAN.package.singR
Author: Liangkang Wang ORCID iD [aut, cre], Irina Gaynanova ORCID iD [aut], Benjamin Risk ORCID iD [aut]
Maintainer: Liangkang Wang <liangkang_wang at brown.edu>
License: MIT + file LICENSE
NeedsCompilation: yes
Citation: singR citation info
CRAN checks: singR results

Documentation:

Reference manual: singR.pdf
Vignettes: singR-tutorial

Downloads:

Package source: singR_0.1.2.tar.gz
Windows binaries: r-devel: singR_0.1.2.zip, r-release: singR_0.1.2.zip, r-oldrel: singR_0.1.2.zip
macOS binaries: r-release (arm64): singR_0.1.2.tgz, r-oldrel (arm64): singR_0.1.2.tgz, r-release (x86_64): singR_0.1.2.tgz, r-oldrel (x86_64): singR_0.1.2.tgz
Old sources: singR archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=singR to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.