Tuning of the alpha generalised correlations between two compositional datasets | R Documentation |

Tuning of the alpha generalised correlations between two compositional datasets.

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

`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. |

The *α*-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 *α* that maximizes the
product of the eigenvalues. If type = "cancor2" the function returns the value
of *α* that maximizes the the largest eigenvalue.

A list including:

`alfa` |
The optimal value of |

`acor` |
The maximum value of the acor. |

`runtime` |
The runtime of the optimization |

Michail Tsagris.

R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.

```
acor, alfa.profile, alfa, alfainv
```

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

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