emulator: Bayesian emulation of computer programs
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 first point of reference.
Downloads:
Reverse dependencies: