largest.kappas

Function <code>largest.kappas</code> calculates the condition numbers for all subcompositions of a given size, for a particular compositional data set.

multivariate

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.

Jan Graffelman

ToolsForCoDa

Multivariate Tools for Compositional Data Analysis

largest.kappas function

<dl> <dt>Xcom</dt>
<dd>A data matrix with compositions in rows</dd> <dt>nparts</dt>
<dd>The number of parts for the subcompositions to be analysed.</dd> <dt>sizetoplist</dt>
<dd>The length of the list of the "best" subcompositions</dd></dl>

Arguments

Jan Graffelman (jan.graffelman@upc.edu)

Author

Calculate condition indices for subcompositions — largest.kappas

<dl>

 <dt>Xcom</dt>
<dd>A data matrix with compositions in rows</dd>

 <dt>nparts</dt>
<dd>The number of parts for the subcompositions to be analysed.</dd>

 <dt>sizetoplist</dt>
<dd>The length of the list of the "best" subcompositions</dd>

</dl>

largest.kappas: Calculate condition indices for subcompositions

Description

Usage

Value

Arguments

Author

Details

Examples