psvd
Eigendecomposition, Singular-Values and the Power Method
For a data matrix with m rows and n columns (m>=n), the power method is used to compute, simultaneously, the eigendecomposition of a square symmetric matrix. This result is used to obtain the singular value decomposition (SVD) and the principal component analysis (PCA) results. Compared to the classical SVD method, the first r singular values can be computed.
- Version0.1-0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release10/25/2024
Team
Doulaye Dembele
Insights
Last 30 days
This package has been downloaded 372 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 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,421 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Apr 01, 2025 with 53 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.
Data provided by CRAN