R: relative difference between covariance matrices

rdcm {robCompositions} | R Documentation

## relative difference between covariance matrices

### Description

The sample covariance matrices are computed with the same isometric transformed observations.

### 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, vol 54 (12), pages 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, 54 (12) 3095-3107.

### See Also

`rdcm`

### Examples

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

[Package robCompositions version 2.0.6 Index]