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clustMD (version 1.0)

ObsLogLikelihood: Approximates the observed log likelihood.

Description

Internal function.

Usage

ObsLogLikelihood(N, CnsIndx, G, Y, mu, Sigma, pi.vec, J, 
OrdIndx, K, perc.cut, Nnorms, zlimits, nom.ind.Z)

Arguments

N
The number of observations.
CnsIndx
The number of continuous variables.
G
The number of mixture components.
Y
An N x J data matrix.
mu
A D x G matrix of means.
Sigma
A D x D x G array of covariance parameters.
pi.vec
The mixing weights.
J
The number of variables.
OrdIndx
The number of continuous and ordinal (including binary) variables.
K
The number of levels for each variable.
perc.cut
Threshold parameters.
Nnorms
The number of Monte Carlo samples.
zlimits
The truncation points given each response.
nom.ind.Z
A list indicating the latent dimensions corresponding to each nominal variable.

Value

  • Output required for clustMD function.

Details

ObsLogLikelihood: 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