model

Oakley's simple model, used as an example for proof-of-concept

models

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.

model: Simple model for concept checking

Description

Usage

Arguments

Examples