R: Tuning of the alpha-generalised correlations between two...

Tuning of the alpha-generalised correlations between two compositional datasets {Compositional}

R Documentation

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 mtsagris@uoc.gr.

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

Examples

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

[Package Compositional version 6.9 Index]

Tuning of the \alpha-generalised correlations between two compositional datasets