summary.netcmc

This function takes a netcmc object and returns a summary of the fitted model.
The summary includes, for selected parameters, posterior medians 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-network generalised linear mixed models for areal unit and network data, with inference in a Bayesian setting using Markov chain Monte Carlo (MCMC) simulation. The response variable can be binomial, Gaussian, or Poisson. Spatial autocorrelation is modelled by a set of random effects that are assigned a conditional autoregressive (CAR) prior distribution following the Leroux model (Leroux et al. (2000) <doi:10.1007/978-1-4612-1284-3_4>). Network structures are modelled by a set of random effects that reflect a multiple membership structure (Browne et al. (2001) <doi:10.1177/1471082X0100100202>).

George Gerogiannis

netcmc

Spatio-Network Generalised Linear Mixed Models for Areal Unit
and Network Data

summary.netcmc function

<dl>
 <dt>object</dt>
<dd>A netcmc fitted model object.</dd> 
 <dt>...</dt>
<dd>Ignored.s</dd> 
</dl>

Arguments

Author

A function that gets a summary of the fitted model. — summary.netcmc

<dl>


 <dt>object</dt>
<dd>A netcmc fitted model object.</dd>

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

 
</dl>

summary.netcmc: A function that gets a summary of the fitted model.

Description

Usage

Value

Arguments

Author