emulator-package {emulator} | R Documentation |
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.
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()
.
Robin K. S. Hankin
Maintainer: <r.hankin@noc.soton.ac.uk>
# 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)