Bayesian emulation of computer programs
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.