View source: R/aeqdist.etest.R
Energy test of equality of distributions using the alpha-transformation | R Documentation |
Energy test of equality of distributions using the α-transformation.
aeqdist.etest(x, sizes, a = 1, R = 999)
x |
A matrix with the compositional data with all groups stacked one under the other. |
sizes |
A numeric vector matrix with the sample sizes. |
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. If more than one values are supplied the energy distance of equality of distributions is applied for each value of α. |
R |
The number of permutations to apply in order to compute the approximate p-value. |
The α-transformation is applied to each composition and then the energy distance of equality of distributions is applied for each value of α or for the single value of α.
A numerical value or a numerical vector, depending on the length of the values of α, with the approximate p-value(s) of the energy test.
Michail Tsagris.
R implementation and documentation: Michail Tsagris mtsagris@uoc.gr.
Szekely, G. J. and Rizzo, M. L. (2004) Testing for Equal Distributions in High Dimension. InterStat, November (5).
Szekely, G. J. (2000) Technical Report 03-05: E-statistics: Energy of Statistical Samples. Department of Mathematics and Statistics, Bowling Green State University.
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
acor, acor.tune, alfa, alfa.profile
y <- rdiri(50, c(3, 4, 5) ) x <- rdiri(60, c(3, 4, 5) ) aeqdist.etest( rbind(x, y), c(dim(x)[1], dim(y)[1]), a = c(-1, 0, 1) )
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