Package: emulator
Type: Package
Title: Bayesian Emulation of Computer Programs
Version: 1.2-21
Authors@R: person(given=c("Robin", "K. S."), family="Hankin", role = c("aut","cre"), email="hankin.robin@gmail.com", comment = c(ORCID = "0000-0001-5982-0415"))
VignetteBuilder: knitr
Depends: R (>= 3.0.1), mvtnorm
Suggests: knitr,rmarkdown
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
Description:
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.
License: GPL
URL: https://github.com/RobinHankin/emulator
BugReports: https://github.com/RobinHankin/emulator/issues
NeedsCompilation: no
Packaged: 2021-04-24 20:28:41 UTC; rhankin
Author: Robin K. S. Hankin [aut, cre] (<https://orcid.org/0000-0001-5982-0415>)
Repository: CRAN
Date/Publication: 2021-04-25 04:20:02 UTC

Package: emulator
Type: Package
Title: Bayesian emulation of computer programs
Version: 1.2-4
Date: 28 June 2009
Author: Robin K. S. Hankin
Depends: R (>= 2.0.0), mvtnorm
Maintainer: Robin K. S. Hankin <hankin.robin@gmail.com>
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 first point of reference.
License: GPL
Packaged: 2011-03-17 07:23:11 UTC; rksh
Repository: CRAN
Date/Publication: 2011-03-18 07:31:47