estimators: Return Maximum A Posteriori (MAP) and Mean A Posteriori...

In CaliCo: Code Calibration in a Bayesian Framework

Description

estimators is a function that returns a list of two elements which are the MAP and the Mean A Posteriori

Usage

estimators(modelfit)

Arguments

modelfit

a calibrate.class object

Value

return a list:

• MAP The Maximum A Posteriori

• MEAN The Mean A Posteriori

Author(s)

M. Carmassi

See Also

model, prior, calibrate, sequentialDesign

Examples

## Not run: 
###################### The code to calibrate
X <- cbind(seq(0,1,length.out=10),seq(0,1,length.out=10))
code <- function(X,theta)
{
  return((6*X[,1]*theta[2]-2)^2*theta[1]*sin(theta[3]*X[,2]-4))
}
Yexp <- code(X,c(1,1,11))+rnorm(10,0,0.1)

############### For the first model
###### Definition of the model
md <- model(code,X,Yexp,"model1")
###### Definition of the prior densities
pr <- prior(type.prior=c("gaussian","gaussian","gaussian","gamma"),opt.prior=
list(c(1,0.01),c(1,0.01),c(11,3),c(2,0.1)))
###### Definition of the calibration options
opt.estim=list(Ngibbs=200,Nmh=600,thetaInit=c(1,1,11,0.1),r=c(0.3,0.3),
sig=diag(4),Nchains=1,burnIn=100)
###### Run the calibration
mdfit <- calibrate(md,pr,opt.estim)
estimators(mdfit)

## End(Not run)

CaliCo documentation built on May 2, 2019, 4:05 p.m.