aitdist: The alpha-IT-distance

In Compositional: Compositional Data Analysis

The α-IT-distance

Description

This is the Euclidean (or Manhattan) distance after the α-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 α=0, the isometric log-ratio transformation is applied.
type	Which type distance do you want to calculate after the α-transformation, "euclidean", or "manhattan".
square	In the case of the Euclidean distance, you can choose to return the squared distance by setting this TRUE.

Details

The α-IT-transformation is applied to the compositional data first and then the Euclidean or the Manhattan distance is calculated.

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.

Author(s)

Michail Tsagris.

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

References

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

See Also

ait, alfadist, alfa

Examples

library(MASS)
x <- as.matrix(fgl[1:20, 2:9])
x <- x / rowSums(x)
aitdist(x, 0.1)
aitdist(x, 1)

Compositional documentation built on July 8, 2022, 1:06 a.m.