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Compositional (version 5.5)

Tuning of the alpha generalised correlations between two compositional datasets: Tuning of the alpha generalised correlations between two compositional datasets

Description

Tuning of the alpha generalised correlations between two compositional datasets.

Usage

acor.tune(y, x, a, type = "dcor")

Arguments

y

A matrix with the compositional data.

x

A matrix with the compositional data.

a

The range of values of the power transformation to search for the optimal one. If zero values are present it has to be greater than 0.

type

the type of correlation to compute, the distance correlation ("edist"), the canonical correlation type 1 ("cancor1") or the canonical correlation type 2 ("cancor2"). See details for more information.

Value

A list including:

alfa

The optimal value of \(\alpha\).

acor

The maximum value of the acor.

runtime

The runtime of the optimization

Details

The \(\alpha\)-transformation is applied to each composition and then the distance correlation or the canonical correlation is computed. If type = "cancor1" the function returns the value of \(\alpha\) that maximizes the product of the eigenvalues. If type = "cancor2" the function returns the value of \(\alpha\) that maximizes the the largest eigenvalue.

See Also

acor, alfa.profile, alfa, alfainv

Examples

Run this code
# NOT RUN {
y <- rdiri(30, runif(3) )
x <- rdiri(30, runif(4) )
acor(y, x, a = 0.4)
# }

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