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.
- Version0.1.2
- R versionunknown
- LicenseMIT
- LicenseLICENSE
- Needs compilation?Yes
- singR citation info
- Last release02/09/2024
Documentation
Team
Liangkang Wang
Irina Gaynanova
Show author detailsRolesAuthorBenjamin Risk
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports5 packages
- Suggests4 packages
- Linking To2 packages