lasandrall/SELPCCA: Sparse Canonical Correlation Analysis for Associating Mutiple High Dimensional Data
Sparse canonical correlation analysis method to associate two high dimensional data types. The algorithm obtains linear combinations of subsets of variables for each data type that contribute to overall dependency structure between the data types.
Getting started
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Package details |
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| Author | Haoyu Chen and Sandra E Safo |
| Maintainer | Sandra E. Safo <ssafo@umn.edu> |
| License | GPL (>=2.0) |
| Version | 1.0 |
| URL | https://www.sandraesafo.com/software |
| Package repository | View on GitHub |
| Installation |
Install the latest version of this package by entering the following in R:
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