rdcm: relative difference between covariance matrices

In robCompositions: Compositional Data Analysis

relative difference between covariance matrices

Description

The sample covariance matrices are computed from compositions expressed in the same isometric logratio coordinates.

Usage

rdcm(x, y)

Arguments

x	matrix or data frame
y	matrix or data frame of the same size as x.

Details

The difference in covariance structure is based on the Euclidean distance between both covariance estimations.

Value

the error measures value

Author(s)

Matthias Templ

References

Hron, K. and Templ, M. and Filzmoser, P. (2010) Imputation of missing values for compositional data using classical and robust methods Computational Statistics and Data Analysis, 54 (12), 3095-3107.

Templ, M. and Hron, K. and Filzmoser and Gardlo, A. (2016). Imputation of rounded zeros for high-dimensional compositional data. Chemometrics and Intelligent Laboratory Systems, 155, 183-190.

See Also

rdcm

Examples

data(expenditures)
x <- expenditures
x[1,3] <- NA
xi <- impKNNa(x)$xImp
rdcm(expenditures, xi)

robCompositions documentation built on Aug. 25, 2023, 5:13 p.m.