updatetau: Update the logistic regression parameters in the mixing...

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

Description

The Metropolis-Hastings update step for the logistic regression parameters in the mixing proportions model, using a surrogate proposal distribution.

Usage

updatetau(G, x.mix, lambda, Sigmag, Sigmag.inv, K, gammag, tau, counttau,
  rho)

Arguments

G	The number of clusters being fitted.
x.mix	A matrix of covariates in the mixing proportions model (including dummy variables for any factor covariates), with a column of 1's appended at the front.
lambda	An n x G matrix of mixing proportions.
Sigmag	Covariance matrix of the multivariate normal prior for tau.
Sigmag.inv	The inverse of Sigmag.
K	The cluster membership vector.
gammag	Mean vector of the multivariate normal prior for tau.
tau	A matrix of logistic regression coefficients, with G rows and number of columns equal to the number of covariates in the mixing proportions model plus 1, for the intercept.
counttau	Counter for number of steps for which the proposed tau value was accepted.
rho	Scaling factor to be used to adjust the acceptance rate.

Value

A list:

tau

The returned version of the tau parameter vector.

lambda

The returned version of the lambda matrix.

counttau

The count of the number of acceptances of tau to that point in the MCMC chain.

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.