bayesm (version 2.2-1)

plot.bayesm.mat: Plot Method for Arrays of MCMC Draws

Description

plot.bayesm.mat is an S3 method to plot arrays of MCMC draws. The columns in the array correspond to parameters and the rows to MCMC draws.

Usage

## S3 method for class 'bayesm.mat':
plot(x,names,burnin,tvalues,TRACEPLOT,DEN,INT,CHECK_NDRAWS, ...)

Arguments

x

An object of either S3 class, bayesm.mat, or S3 class, mcmc

names

optional character vector of names for coefficients

burnin

number of draws to discard for burn-in, def: .1*nrow(X)

tvalues

vector of true values

TRACEPLOT

logical, TRUE provide sequence plots of draws and acfs, def: TRUE

DEN

logical, TRUE use density scale on histograms, def: TRUE

INT

logical, TRUE put various intervals and points on graph, def: TRUE

CHECK_NDRAWS

logical, TRUE check that there are at least 100 draws, def: TRUE

...

standard graphics parameters

concept

• MCMC
• S3 method
• plot

Details

Typically, plot.bayesm.mat will be invoked by a call to the generic plot function as in plot(object) where object is of class bayesm.mat. All of the bayesm MCMC routines return draws in this class (see example below). One can also simply invoke plot.bayesm.mat on any valid 2-dim array as in plot.bayesm.mat(betadraws). plot.bayesm.mat paints (by default) on the histogram: green "[]" delimiting 95% Bayesian Credibility Interval yellow "()" showing +/- 2 numerical standard errors red "|" showing posterior mean plot.bayesm.mat is also exported for use as a standard function, as in plot.bayesm.mat(matrix)

Examples

##
## not run
#  out=runiregGibbs(Data,Prior,Mcmc)
#  plot(out$betadraw)
#