rdcm: relative difference between covariance matrices

Description Usage Arguments Details Value Author(s) References See Also Examples

View source: R/rdcm.R

Description

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

Usage

1
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

1
2
3
4
5
data(expenditures)
x <- expenditures
x[1,3] <- NA
xi <- impKNNa(x)$xImp
rdcm(expenditures, xi)

Example output

Loading required package: robustbase
Loading required package: ggplot2
Loading required package: data.table
Loading required package: e1071
Loading required package: pls

Attaching package: 'pls'

The following object is masked from 'package:stats':

    loadings

sROC 0.1-2 loaded

Attaching package: 'robCompositions'

The following object is masked from 'package:robustbase':

    alcohol

[1] 0.002860353

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