acor.tune: Tuning of the alpha-generalised correlations between two...

In Compositional: Compositional Data Analysis

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.

Details

The \alpha-transformation is applied to each composition and then, if type="dcor" 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.

Value

A list including:

alfa	The optimal value of \alpha.
acor	The maximum value of the acor.
runtime	The runtime of the optimization

Author(s)

Michail Tsagris.

R implementation and documentation: Michail Tsagris [e-mail].

References

Tsagris M.T., Preston S. and Wood A.T.A. (2011). A data-based power transformation for compositional data. In Proceedings of the 4th Compositional Data Analysis Workshop, Girona, Spain. https://arxiv.org/pdf/1106.1451.pdf

See Also

acor, alfa.profile, alfa, alfainv

Examples

y <- rdiri(30, runif(3) )
x <- rdiri(30, runif(4) )
acor(y, x, a = 0.4)

Compositional documentation built on Oct. 9, 2024, 5:10 p.m.