updatesigma2: Update variances in each cluster.

In MEclustnet: Fit the Mixture of Experts Latent Position Cluster Model to Network Data

Description

A Gibbs step to update variances in each cluster.

Usage

updatesigma2(G, alpha, m, d, sigma02, z, K, mu, sigma2)

Arguments

G	The number of clusters being fitted.
alpha	Degrees of freedom of the scaled inverse Chi squared prior distribution on the cluster variances.
m	Vector of length G containing the number of nodes in each cluster.
d	Dimension of the latent space.
sigma02	Scaled factor of the scaled inverse Chi squared prior distribution on the cluster variances.
z	The n x d matrix of latent locations.
K	The cluster membership vector.
mu	The G x d matrix of cluster means.
sigma2	The G vector of cluster variances.

Value

The G vector of cluster variances.

References

Isobel Claire Gormley and Thomas Brendan Murphy. (2010) A Mixture of Experts Latent Position Cluster Model for Social Network Data. Statistical Methodology, 7 (3), pp.385-405.

See Also

MEclustnet

MEclustnet documentation built on Oct. 10, 2019, 5:04 p.m.