SAVE (version 1.0)

plot: Plots for an object of class SAVE

Description

Plots are provided to summarize graphically the Bayesian analysis of a computer model.

Usage

"plot"(x, option = "trace", ...)

Arguments

x

An object of class SAVE

option

One of "trace", "calibration" or "precision"(see details)

...

Additional graphical parameters to be passed

Details

Three different plots are implemented. If option="trace" this function returns the trace plots of the simulated chains. This plot is useful for assessing the convergence of the sampling method. If option="calibration" this function plots an histogram of the sample obtained from the posterior distribution of the calibration parameters and a line representing the prior assumed. If option="precision" the histograms and priors correspond to the precision parameters.

Examples

## Not run: 
# library(SAVE)
# 
# #############
# # load data
# #############
# 
# data(spotweldfield,package='SAVE')
# data(spotweldmodel,package='SAVE')
# 
# ##############
# # create the SAVE object which describes the problem and
# # compute the corresponding mle estimates
# ##############
# 
# gfsw <- SAVE(response.name="diameter", controllable.names=c("current", "load", "thickness"), 
# 			 calibration.names="tuning", field.data=spotweldfield, 
# 			 model.data=spotweldmodel, mean.formula=~1, 
# 			 bestguess=list(tuning=4.0))
# 
# ##############
# # obtain the posterior distribution of the unknown parameters
# ##############
# 
# gfsw <- bayesfit(object=gfsw, prior=c(uniform("tuning", upper=8, lower=0.8)), 
# 				 n.iter=20000, n.burnin=100, n.thin=2)
# 
# #A trace plot of the chains
# plot(gfsw, option="trace")
# #The histogram of the posterior density of calibration parameters
# plot(gfsw, option="calibration")
# #The histogram of the posterior density of precision parameters
# plot(gfsw, option="precision")
# 
# ## End(Not run)