ddplot: Distance-Distance Plot

In MN: Matrix Normal Distribution

Distance-Distance Plot

Description

Distance-Distance Plot

Usage

ddplot(X, M, U, V)

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.

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.

Value

A scatter plot of the Mahalanobis distances.

Author(s)

Michail Tsagris and Omar Alzeley.

R implementation and documentation: Michail Tsagris [e-mail] and Omar Alzeley [e-mail].

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)

MN documentation built on June 22, 2024, 11:07 a.m.