Multivariate Tools for Compositional Data Analysis
Canonical correlation analysis.
centring of a data matrix
Centred log-ratio transformation
Calculate condition indices for subcompositions
Logratio Canonical Correlation Analysis
Logratio Linear Discriminant Analysis
Logratio principal component analysis with condition indices
Create a Ternary Plot for three-part Compositions
Compute the trace of a matrix
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>. Functions for log-ratio principal component analysis with condition number computations and log-ratio discriminant analysis have been added to the package.