summary.mcmcSAR: Summarizing Bayesian SAR Model

Description Usage Arguments Details Value Examples

Description

Summary and print methods for the class 'mcmcSAR'.

Usage

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## S3 method for class 'mcmcSAR'
summary(object, alpha = 0.95, plot.type = NULL, burnin = NULL, ...)

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

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

Arguments

object

an object of class "mcmcSAR", output of the function mcmcSAR.

alpha

(optional, default = 0.95), the significance level of parameter.

plot.type

(optional) a character that indicate if the simulations from the posterior distribution should be printed (if 'plot.type = "sim"') or if the posterior distribution densities should be plotted ('plot.type = "dens"'). The plots can also done using the method plot.

burnin

is the 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.

...

further arguments passed to or from other methods.

x

an object of class "summary.mcmcSAR" or "mcmcSAR, output of thes functions summary.mcmcSAR and print.summary.mcmcSAR.

Details

The function is smart and allows all the possible arguments with the functions summary, plot, par... such as 'col', 'lty', 'mfrow'... summary.mcmcSAR, print.summary.mcmcSAR and print.mcmcSAR can be called by summary or print.

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

matrix containing the simulations.

hyperparms

return value of 'hyperparms'.

accept.rate

acceptance rate of zeta.

formula

input value of 'formula'.

alpha

significance level of parameter.

ctrl.mcmc

return value of 'ctrl.mcmc'.

...

arguments passed to methods.

Examples

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## Not run: 
# Let us consider the example from the mcmcSAR function
out1          <- mcmcSAR(y ~ X | X, hyperparms = hyperparms, ctrl.mcmc = ctrl)
# Print the summary
summary(out)
# Print summary with plot and change significance level 
summary(out, alpha = 0.90, plot.type = "sim", col = "blue")
# Print summary with plot and change significance level and the layout of the plot
summary(out, alpha = 0.90, plot.type = "sim", col = "blue", mfrow = c(4, 4))
# All the possible argument with the function summary and the function plot can be passed

## End(Not run)

ahoundetoungan/PartialNetwork documentation built on Oct. 6, 2020, 1:51 a.m.