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It performs Canonical Correlation Analysis and provides inferential guaranties on the correlation components. The p-values are computed following the resampling method developed in Winkler, A. M., Renaud, O., Smith, S. M., & Nichols, T. E. (2020). Permutation inference for canonical correlation analysis. NeuroImage, <doi:10.1016/j.neuroimage.2020.117065>. Furthermore, it provides plotting tools to visualize the results.
| Version: | 0.2 |
| Imports: | methods, stats, ggplot2, plyr |
| Published: | 2022-01-28 |
| DOI: | 10.32614/CRAN.package.acca |
| Author: | Livio Finos |
| Maintainer: | livio finos <livio.finos at unipd.it> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | no |
| CRAN checks: | acca results |
| Reference manual: | acca.pdf |
| Package source: | acca_0.2.tar.gz |
| Windows binaries: | r-devel: acca_0.2.zip, r-release: acca_0.2.zip, r-oldrel: acca_0.2.zip |
| macOS binaries: | r-release (arm64): acca_0.2.tgz, r-oldrel (arm64): acca_0.2.tgz, r-release (x86_64): acca_0.2.tgz, r-oldrel (x86_64): acca_0.2.tgz |
| Old sources: | acca archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.