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

In bayesm: Bayesian Inference for Marketing/Micro-Econometrics

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: 0.1*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

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)

Author(s)

Peter Rossi, Anderson School, UCLA, [e-mail].

Examples

## Not run: out=runiregGibbs(Data,Prior,Mcmc); plot(out$betadraw)

bayesm documentation built on Sept. 24, 2023, 1:07 a.m.