print.CARBayesST

This function takes a CARBayesST object and returns a summary of the fitted model.
The summary includes, for selected parameters, posterior means and 95 percent 
credible intervals, the effective number of independent samples and the Geweke 
convergence diagnostic in the form of a Z-score.

Implements a class of univariate and multivariate spatio-temporal generalised linear mixed models for areal unit data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian, or Poisson, but for some models only the binomial and Poisson data likelihoods are available. The spatio-temporal autocorrelation is modelled by random effects, which are assigned conditional autoregressive (CAR) style prior distributions. A number of different random effects structures are available, including models similar to Rushworth et al. (2014) <doi:10.1016/j.sste.2014.05.001>. Full details are given in the vignette accompanying this package. The creation and development of this package was supported by the Engineering and Physical Sciences Research Council (EPSRC) grants EP/J017442/1 and EP/T004878/1 and the Medical Research Council (MRC) grant MR/L022184/1.

Duncan Lee

CARBayesST

Spatio-Temporal Generalised Linear Mixed Models for Areal Unit
Data

print.CARBayesST function

<dl> <dt>x</dt>
<dd>A CARBayesST fitted model object.</dd> <dt>...</dt>
<dd>Ignored.</dd></dl>

Arguments

Author

Print a summary of the fitted model to the screen. — print.CARBayesST

<dl>

 <dt>x</dt>
<dd>A CARBayesST fitted model object.</dd>

 <dt>...</dt>
<dd>Ignored.</dd>

</dl>

print.CARBayesST: Print a summary of the fitted model to the screen.

Description

Usage

Arguments

Author