updatebeta {MEclustnet}

Update the logistic regression parameters in the link probabilities model.

Description

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

Usage

updatebeta(beta, p, x.link, delta, y, epsilon, psi, psi.inv, pis,
  countbeta, rho, n.tilde)

Arguments

beta

Vector of regression coefficients in the link probabilities.

p

Length of beta.

x.link

Matrix, with n^2 - n rows and the same number of columns as covariates (including the intercept), giving the differences in covariates for all pairs of nodes.

delta

Vector of Euclidean distances between locations in the latent space of all pairs of nodes.

y

Vector version of the adjacency matrix, with the diagonal removed.

epsilon

Mean of the multivariate normal prior on beta.

psi

Covariance of the multivariate normal prior on beta.

psi.inv

Inverse covariance of the multivariate normal prior on beta.

pis

Vector of length n^2 - n providing the link probabilities between all pairs of nodes.

countbeta

Counter for number of steps for which the proposed beta value was accepted.

rho

Scaling factor to be used to adjust the acceptance rate.

n.tilde

Length of the vector version of the adjacency matrix, with the diagonal removed i.e. n^2 - n.

Details

See appendix of the paper detailed below for details.

Value

A list:

beta

The returned version of the beta parameter vector.

countbeta

The count of the number of acceptances of beta 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