Compositional (version 5.4)

The alpha-IT-distance: The \(\alpha\)-IT-distance

Description

This is the Euclidean (or Manhattan) distance after the \(\alpha\)-IT-transformation has been applied.

Usage

aitdist(x, a, type = "euclidean", square = FALSE)
aitdista(xnew, x, a, type = "euclidean", square = FALSE)

Arguments

xnew

A matrix or a vector with new compositional data.

x

A matrix with the compositional data.

a

The value of the power transformation, it has to be between -1 and 1. If zero values are present it has to be greater than 0. If \(\alpha=0\), the isometric log-ratio transformation is applied.

type

Which type distance do you want to calculate after the \(\alpha\)-transformation, "euclidean", or "manhattan".

square

In the case of the Euclidean distance, you can choose to return the squared distance by setting this TRUE.

Value

For "alfadist" a matrix including the pairwise distances of all observations or the distances between xnew and x. For "alfadista" a matrix including the pairwise distances of all observations or the distances between xnew and x.

Details

The \(\alpha\)-IT-transformation is applied to the compositional data first and then the Euclidean or the Manhattan distance is calculated.

References

Clarotto L., Allard D. and Menafoglio A. (2021). A new class of \(\alpha\)-transformations for the spatial analysis of Compositional Data. https://arxiv.org/abs/2110.07967

See Also

ait, alfadist, alfa

Examples

# NOT RUN {
library(MASS)
x <- as.matrix(fgl[1:20, 2:9])
x <- x / rowSums(x)
aitdist(x, 0.1)
aitdist(x, 1)
# }