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emulator: Bayesian Emulation of Computer Programs
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 techniques 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 posterior
estimates of the PDF of the output of a model, conditioned on results
from previous runs and a user-specified prior linear model. The
package includes functionality to evaluate quadratic forms
efficiently.
Documentation:
Downloads:
Reverse dependencies:
Linking:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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