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Compute efficiently (via Fortran code) the means, covariance and scattering matrices conditioning on a weighted or indicator matrix

covw(X, Z, normalize = TRUE)

A list with the following components:

A \((p x G)\) matrix of weighted means.

A \((p x p x G)\) array of weighted covariance matrices.

A \((p x p x G)\) array of weighted scattering matrices.

A \((n x p)\) data matrix, with \(n\) observations on \(p\) variables.

A \((n x G)\) matrix of weights, with \(G\) number of groups.

A logical indicating if rows of Z should be normalized to sum to one.

Z

M. Fop and L. Scrucca

# Z as an indicator matrix X <- iris[,1:4] Z <- unmap(iris$Species) str(covw(X, Z)) # Z as a matrix of weights mod <- Mclust(X, G = 3, modelNames = "VVV") str(covw(X, mod$z))

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