SAVE (version 1.0)

plot.predictreality.SAVE: A function for plotting summaries of an object of class predictreality.SAVE.

Description

Two different plots to summarize graphically the results in an object of class predictreality.SAVE.

Usage

"plot"(x, option = "trace", ...)

Arguments

x

An object of class predictreality.SAVE

option

One of "biascorr" or "biasfun" (see details)

...

Additional graphical parameters to be passed

Details

If option="biascorr" this function returns a plot with point predictions and 95% tolerance bounds of reality at the given set of controllable inputs. If option="biasfun" the plot represents the estimated bias and 95% credible bounds.

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)
# 
# #########
# # bias-corrected prediction at a set of inputs
# # using predictreality
# ##########
# 
# load <- c(4.0,5.3)
# curr <- seq(from=20,to=30,length=20)
# g <- c(1,2)
# 
# xnew<- expand.grid(current = curr, load = load, thickness=g)
# 
# # Obtain samples
# prsw <- predictreality(object=gfsw, newdesign=xnew, tol=1.E-12)
# 
# #Plot the results:
# #Represent reality and tolerance bounds:
# plot(prsw, option="biascorr")
# #Represent bias and tolerance bounds:
# plot(prsw, option="biasfun")
# 
# 
# ## End(Not run)