Internal function.
M.step(
tau,
N,
sumTauEz,
J,
OrdIndx,
D,
G,
Y,
CnsIndx,
sumTauS,
model,
a,
nom.ind.Z
)Output required for clustMD function.
a N x G matrix of cluster membership probabilities.
number of observations.
the sum across all observations of observed and expected latent continuous values mutiplied by the posterior probability of belonging to each cluster.
the number of variables.
the sum of the number of continuous and ordinal (including binary) variables.
dimension of the latent data.
the number of mixture components.
a N x J data matrix.
the number of continuous variables.
the sum across all observations of outer product of observed and expected latent continuous values mutiplied by the posterior probability of belonging to each cluster.
which clustMD covariance model is fitted.
a G x D matrix of the entries of A.
the latent dimensions corresponding to each nominal variable.
clustMD