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Provides functions for multivariate analysis with compositional data. Includes a function for doing compositional canonical correlation analysis. This analysis requires two data matrices of compositions, which can be adequately transformed and used as entries in a specialized program for canonical correlation analysis, that is able to deal with singular covariance matrices. The methodology is described in Graffelman et al. (2017) <doi:10.1101/144584>. A function for log-ratio principal component analysis with condition number computations has been added to the package.
Version: | 1.0.6 |
Depends: | R (≥ 1.8.0), MASS, calibrate, HardyWeinberg |
Published: | 2021-09-20 |
Author: | Jan Graffelman |
Maintainer: | Jan Graffelman <jan.graffelman at upc.edu> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | www.R-project.org, http://www-eio.upc.edu/~jan/ |
NeedsCompilation: | no |
Citation: | ToolsForCoDa citation info |
CRAN checks: | ToolsForCoDa results |
Reference manual: | ToolsForCoDa.pdf |
Vignettes: |
Multivariate tools for compositional data analysis: the \pkg{ToolsForCoDA} package |
Package source: | ToolsForCoDa_1.0.6.tar.gz |
Windows binaries: | r-devel: ToolsForCoDa_1.0.6.zip, r-release: ToolsForCoDa_1.0.6.zip, r-oldrel: ToolsForCoDa_1.0.6.zip |
macOS binaries: | r-release (arm64): ToolsForCoDa_1.0.6.tgz, r-oldrel (arm64): ToolsForCoDa_1.0.6.tgz, r-release (x86_64): ToolsForCoDa_1.0.6.tgz, r-oldrel (x86_64): ToolsForCoDa_1.0.6.tgz |
Old sources: | ToolsForCoDa 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.
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