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clustMD (version 1.0)

M.step: M-step of the (MC)EM algorithm.

Description

Internal function.

Usage

M.step(tau, N, Elz, J, OrdIndx, D, G, Y, CnsIndx, S2, model, a)

Arguments

tau
An N x G matrix of conditional cluster membership probabilities.
N
Number of observations.
Elz
A N x D x G array of expected values of cluster labels multiplied by the latent data.
J
The number of variables.
OrdIndx
The number of continuous and ordinal (including binary) variables.
D
Dimension of the latent data.
G
The number of mixture components.
Y
A N x J data matrix.
CnsIndx
The number of continuous variables.
S2
A N x D x G array of expected values of the latent data squared.
model
Which clustMD model is fitted.
a
A G x D matrix of the entries of A.

Value

  • Output required for clustMD function.

Details

M-step: an internal function.

References

McParland, D. and Gormley, I.C. (2014). Model based clustering for mixed data: clustMD. Technical report, University College Dublin.

See Also

clustMD