Computation of all pairwise logratios.

logratio

Univariate and multivariate methods for compositional data
analysis, based on logratios. The package implements the approach in the
book Compositional Data Analysis in Practice by Michael Greenacre (2018),
where accent is given to simple pairwise logratios. Selection can be made
of logratios that account for a maximum percentage of logratio variance.
Various multivariate analyses of logratios are included in the package.

Michael Greenacre

easyCODA

Compositional Data Analysis in Practice

LR function

<dl> <dt>data</dt>
<dd>A compositional data frame or matrix</dd> <dt>ordering</dt>
<dd>A permutation of the columns (default: the original ordering)</dd> <dt>weight</dt>
<dd>Logical indicating if varying weights are returned (default:<code>TRUE</code>). If <code>FALSE</code>, unweighted (equal) weights are returned. Alternatively a set of positive weights can be specified.</dd></dl>

Arguments

Author

All pairwise logratios — LR

<dl>

 <dt>data</dt>
<dd>A compositional data frame or matrix</dd>

 <dt>ordering</dt>
<dd>A permutation of the columns (default: the original ordering)</dd>

 <dt>weight</dt>
<dd>Logical indicating if varying weights are returned (default:<code>TRUE</code>). If <code>FALSE</code>, unweighted (equal) weights are returned. Alternatively a set of positive weights can be specified.</dd>

</dl>

LR: All pairwise logratios

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples