RGCCA

Regularized and Sparse Generalized Canonical Correlation Analysis for Multiblock Data

CRAN Package

Multi-block data analysis concerns the analysis of several sets of variables (blocks) observed on the same group of individuals. The main aims of the RGCCA package are: to study the relationships between blocks and to identify subsets of variables of each block which are active in their relationships with the other blocks. This package allows to (i) run R/SGCCA and related methods, (ii) help the user to find out the optimal parameters for R/SGCCA such as regularization parameters (tau or sparsity), (iii) evaluate the stability of the RGCCA results and their significance, (iv) build predictive models from the R/SGCCA. (v) Generic print() and plot() functions apply to all these functionalities.


Documentation


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Insights

Last 30 days

This package has been downloaded 496 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 17 times.

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0 downloadsMar 2, 2025
13 downloadsMar 3, 2025
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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 5,949 times in the last 365 days. That's a lot of interest! Someone might even write a blog post about it. The day with the most downloads was Jun 04, 2024 with 68 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


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Dependencies

  • Imports9 packages
  • Suggests8 packages
  • Reverse Suggests2 packages