plot.mcmcSAR {PartialNetwork}

Plotting estimation of Bayesian SAR model

Description

Plotting the simulation from the posterior distribution as well as the density functions of Bayesian SAR model parameter. For more details about the graphical parameter arguments, see par.

Usage

## S3 method for class 'mcmcSAR'
plot(x, plot.type = "sim", burnin = NULL, which.parms = "theta", ...)

## S3 method for class 'plot.mcmcSAR'
print(x, ...)

Arguments

x

object of class "mcmcSAR", output of the function mcmcSAR or object of class "plot.mcmcSAR", output of the function plot.mcmcSAR.

plot.type

character indicating the type of plot: "sim" for plotting the simulation from the posterior distribution or "dens" for plotting the posterior density functions.

burnin

number of MCMC steps which will be considered as burn-in iterations. If NULL (default value), the 50% first MCMC steps performed are used as burn-in iterations.

which.parms

character indicating the parameters whose the posterior distribution will be plotted: "theta" for the parameters of the outcome model and "rho" for the parameters of the network formation model.

...

arguments to be passed to methods, such as par.

Value

A list consisting of:

n.group

number of groups.

N

vector of each group size.

iteration

number of MCMC steps performed.

burnin

number of MCMC steps which will be considered as burn-in iterations.

posterior

summary of the posterior distribution to be plotted.

hyperparms

return value of hyperparms.

accept.rate

acceptance rate of zeta.

propG0.obs

proportion of observed network data.

method.net

network formation model specification.

formula

input value of formula.

ctrl.mcmc

return value of ctrl.mcmc.

which.parms

return value of which.parms.

plot.type

type of the plot.

...

arguments passed to methods.