invSLR

Given a full set of amalgamation (or summation) balances (SLRs), compute the inverse (i.e. recover the original parts)

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

invSLR function

<dl> <dt>SLRmatrix</dt>
<dd>A matrix of amalgamation logratios, one less column than the number of parts</dd> <dt>part.names</dt>
<dd>Part names in the reconstructed compositional data matrix</dd> <dt>ratio.names</dt>
<dd>Definition of the amalgamation logratios</dd></dl>

Arguments

Author

Inverse of full set of amalgamation balances — invSLR

<dl>

 <dt>SLRmatrix</dt>
<dd>A matrix of amalgamation logratios, one less column than the number of parts</dd>

 <dt>part.names</dt>
<dd>Part names in the reconstructed compositional data matrix</dd>

 <dt>ratio.names</dt>
<dd>Definition of the amalgamation logratios</dd>

</dl>

invSLR: Inverse of full set of amalgamation balances

Description

Usage

Value

Arguments

Author

Details

References

See Also

Examples