BACCO (version 1.0-50)

emulator-package: Emulation of computer code output

Description

This package allows one to estimate the output of a computer program, as a function of the input parameters, without actually running it. The computer program is assumed to be a Gaussian process, whose parameters are estimated using Bayesian techniqes that give a PDF of expected program output. This PDF is conditional on a training set of runs, each consisting of a point in parameter space and the model output at that point. The emphasis is on complex codes that take weeks or months to run, and that have a large number of undetermined input parameters; many climate prediction models fall into this class. The emulator essentially determines Bayesian a-postiori estimates of the PDF of the output of a model, conditioned on results from previous runs and a user-specified prior linear model. A working example is given in the help page for function interpolant(), which should be the users's first point of reference.

Details

ll{ Package: emulator Type: Package Version: 1.0 Date: 2007-05-02 License: What license is it under? }

The primary function of the package is interpolant().

References

J. Oakley 1999. Bayesian uncertainty analysis for complex computer codes, PhD thesis, University of Sheffield.

J. Oakley and A. O'Hagan, 2002. Bayesian Inference for the Uncertainty Distribution of Computer Model Outputs, Biometrika 89(4), pp769-784 R. K. S. Hankin 2005. Introducing BACCO, an R bundle for Bayesian analysis of computer code output, Journal of Statistical Software, 14(16)

Examples

# The following example takes a toy dataframe (toy), which represents an
#  experimental design.  Variable d contains observations at points in a
#  six dimensional parameter space specified by the rows of toy.
#  Function interpolant() is then called to estimate what the
#  observation would be at a point that has no direct observation.


data(toy)
d <- c(11.05, 7.48, 12.94, 14.91, 11.34, 5.0, 11.83, 11.761, 11.62, 6.70)
fish <- rep(1,6)
x <- rep(0.5, 6)
interpolant(x, d, toy, scales=fish,give=TRUE)