z.moments_diag: Calculates the first and second moments of the latent data...

In clustMD: Model Based Clustering for Mixed Data

Description

Internal function.

Usage

z.moments_diag(D, G, N, CnsIndx, OrdIndx, zlimits, mu, Sigma, Y, J, K, norms,
  nom.ind.Z)

Arguments

D	dimension of the latent data.
G	number of mixture components.
N	number of observations.
CnsIndx	the number of continuous variables.
OrdIndx	the sum of the number of continuous and ordinal (including binary) variables.
zlimits	the truncation points for the latent data.
mu	a D x G matrix of means.
Sigma	a D x D x G array of covariance parameters.
Y	an N x J data matrix.
J	the number of variables.
K	the number of levels for each variable.
norms	a matrix of standard normal deviates.
nom.ind.Z	the latent dimensions corresponding to each nominal variable.

Value

Output required for clustMD function.

See Also

clustMD

clustMD documentation built on May 2, 2019, 2:09 a.m.