ToolsForCoDa: Multivariate Tools for Compositional Data Analysis

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.

Package details

AuthorJan Graffelman <>
MaintainerJan Graffelman <>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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ToolsForCoDa documentation built on Sept. 20, 2021, 5:19 p.m.