R: relative difference between covariance matrices

rdcm {robCompositions} | R Documentation

## 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)

[Package robCompositions version 2.3.1 Index]