variation: Robust and classical variation matrix

Description Usage Arguments Details Value Author(s) References Examples

Description

Estimates the variation matrix with robust methods.

Usage

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variation(x, method = "robustPivot")

Arguments

x

data frame or matrix with positive entries

method

method used for estimating covariances. See details.

Details

The variation matrix is estimated for a given compositional data set. Instead of using the classical standard deviations the miniminm covariance estimator is used (covMcd) is used when parameter robust is set to TRUE.

For method robustPivot forumala 5.8. of the book (see second reference) is used. Here robust (mcd-based) covariance estimation is done on pivot coordinates. Method robustPairwise uses a mcd covariance estimation on pairwise log-ratios. Methods Pivot (see second reference) and Pairwise (see first reference) are the non-robust counterparts. Naturally, Pivot and Pairwise gives the same results, but the computational time is much less for method Pairwise.

Value

The (robust) variation matrix.

Author(s)

Karel Hron, Matthias Templ

References

Aitchison, J. (1986) The Statistical Analysis of Compositional Data Monographs on Statistics and Applied Probability. Chapman \& Hall Ltd., London (UK). 416p.

#' Filzmoser, P., Hron, K., Templ, M. (2018) Applied Compositional Data Analysis. Springer, Cham.

Examples

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data(expenditures)
variation(expenditures) # default is method "robustPivot"
variation(expenditures, method = "Pivot")
variation(expenditures, method = "robustPairwise")
variation(expenditures, method = "Pairwise") # same results as Pivot

robCompositions documentation built on Jan. 13, 2021, 10:07 p.m.