singR

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).

Last 30 days

This package has been downloaded 202 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 2 times.

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Last 365 days

This package has been downloaded 31,977 times in the last 365 days. That's enough downloads to make it mildly famous in niche technical communities. A badge of honor! The day with the most downloads was Apr 09, 2024 with 895 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.