centres the columns of a matrix to mean zero.

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

cen function

<dl> <dt>X</dt>
<dd>a raw data matrix.</dd> <dt>w</dt>
<dd>a vector of case weights.</dd></dl>

Arguments

Jan Graffelman (jan.graffelman@upc.edu)

Author

centring of a data matrix — cen

<dl>

 <dt>X</dt>
<dd>a raw data matrix.</dd>

 <dt>w</dt>
<dd>a vector of case weights.</dd>

</dl>

cen: centring of a data matrix

Description

Usage

Value

Arguments

Author

Examples