MN (version 1.0)

Distance-Distance Plot: Distance-Distance Plot

Description

Distance-Distance Plot

Usage

ddplot(X, M, U, V)

Value

A scatter plot of the Mahalanobis distances.

Arguments

X

A list with k elements, k matrices of dimension \(n \ times p\) each. In the case of one matrix only, this may be given as a numerical matrix and not as an element in a list.

M

The mean matrix of the distribution, a numerical matrix of dimensions \(n \times p\).

U

The covariance matrix associated with the rows, a numerical matrix of dimensions \(n \times n\).

V

The covariance matrix associated with the columns, a numerical matrix of dimensions \(p \times p\).

Author

Michail Tsagris and Omar Alzeley.

R implementation and documentation: Michail Tsagris and Omar Alzeley .

Details

The distance-distance plot is produced. This is a scatter plot of the Mahalanobis distances computed using the estimated parameters from the multivariate normal and matrix normal distribution. See Pocuca et al. (2019) for more details.

References

Pocuca N., Gallaugher M. P., Clark K. M. & McNicholas P. D. (2019). Assessing and Visualizing Matrix Variate Normality. arXiv:1910.02859.

See Also

rmn, mn.mle, dmn, ddkstest

Examples

M <- as.matrix(iris[1:8, 1:4])
U <- cov( matrix( rnorm(100 * 8), ncol = 8 ) )
V <- cov( iris[1:50, 1:4] )
X <- rmn(100, M, U, V)
ddplot(X, M, U, V)