M-step of the (MC)EM algorithm.

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Description

Internal function.

Usage

1
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.

Details

M-step: an internal function.

Value

Output required for clustMD function.

Note

An internal function.

Author(s)

Damien McParland

References

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

See Also

clustMD