expert.estimates

A dataframe consisting of expert judgements of low, best, and high
values for each of 19 variables that are used in the creation of
the <code>QWERTYgoin.*</code> files by <code>makeinputfiles()</code>.

datasets


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.  A vignette is
provided and the help pages include examples.

Robin K S Hankin

emulator

Bayesian Emulation of Computer Programs

expert.estimates function

A data frame with 19 observations on the following 3 variables.<dl class="dl-horizontal">
 <dt>low</dt><dd>a numeric vector: low estimate</dd>
 <dt>best</dt><dd>a numeric vector: best estimate</dd>
 <dt>high</dt><dd>a numeric vector: high estimate</dd>
 </dl>

Format

Expert estimates for Goldstein input parameters — expert.estimates

A data frame with 19 observations on the following 3 variables.<dl class='dl-horizontal'>
 <dt>low</dt><dd>a numeric vector: low estimate</dd>
 <dt>best</dt><dd>a numeric vector: best estimate</dd>
 <dt>high</dt><dd>a numeric vector: high estimate</dd>
 </dl>

expert.estimates: Expert estimates for Goldstein input parameters

Description

Usage

Arguments

Format

Details

Examples