The k-nearest neighbours using the alpha-distance {Compositional}

The k-nearest neighbours using the \alpha-distance

Description

The k-nearest neighbours using the \alpha-distance.

Usage

alfann(xnew, x, a, k = 10, rann = 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.

k

The number of nearest neighbours to search for.

rann

If you have large scale datasets and want a faster k-NN search, you can use kd-trees implemented in the R package "Rnanoflann". In this case you must set this argument equal to TRUE. Note however, that in this case, the only available distance is by default "euclidean".

Details

The \alpha-transformation is applied to the compositional data first and the indices of the k-nearest neighbours using the Euclidean distance are returned.

Value

A matrix including the indices of the nearest neighbours of each xnew from x.

Author(s)

Michail Tsagris.

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

References

MTsagris M., Alenazi A. and Stewart C. (2023). Flexible non-parametric regression models for compositional response data with zeros. Statistics and Computing, 33(106).

https://link.springer.com/article/10.1007/s11222-023-10277-5

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

alfa.knn, comp.nb, alfa.rda, alfa.nb, link{aknn.reg}, alfa, alfainv

Examples

library(MASS)
xnew <- as.matrix(fgl[1:20, 2:9])
xnew <- xnew / rowSums(xnew)
x <- as.matrix(fgl[-c(1:20), 2:9])
x <- x / rowSums(x)
b <- alfann(xnew, x, a = 0.1, k = 10)