| Ra {GLMMGibbs} | R Documentation |
Create a random factor to be used in the glmm
function for fitting generalised linear mixed models by
Gibbs sampling
Ra(data, shape=0.001, scale=0.001, type="identity", contrast="identity", map="none", zlevel=1, of.interest=FALSE)
Ra returns an a factor, which when included in the model
passed to the glmm
function, is treated as a random effect.
The effect values have a multivariate normal prior with mean zero and a covariance matrix which depends on the `type' of random effect and the parameterisation being used. Its inverse is the product of a fixed matrix and a random scalar hyperparameter, which has a gamma prior distribution with given shape and scale parameters.
Full details are given in the document
"GLMMGibbs: An R Package for Estimating Bayesian Generalised
Linear Mixed Models by Gibbs Sampling", supplied with this package.
A value of class factor, but with additional attributes.
Jonathan Myles, Imperial Cancer Research Fund, and David Clayton, Wellcome Trust mylesj@icrf.icnet.uk
Clayton, D.G. (1996) Generalized Linear Mixed Models in em Ph{Markov chain Monte Carlo in Practice}, ed. Gilks, W. R. and Richardson, S. and and Spiegelhalter, D. J., Chapman & Hall.