emulator-package |
Bayesian Emulation of Computer Programs |
betahat.fun |
Calculates MLE coefficients of linear fit |
betahat.fun.A |
Calculates MLE coefficients of linear fit |
cond.sample |
Implementation of the ideas of Oakley and O'Hagan 2002 |
corr |
correlation function for calculating A |
corr.matrix |
correlation function for calculating A |
cprod |
Evaluate a quadratic form efficiently |
emulator |
Bayesian Emulation of Computer Programs |
estimator |
Estimates each known datapoint using the others as datapoints |
expert.estimates |
Expert estimates for Goldstein input parameters |
ht |
Evaluate a quadratic form efficiently |
int.qq |
Interpolates between known points using Bayesian estimation |
interpolant |
Interpolates between known points using Bayesian estimation |
interpolant.quick |
Interpolates between known points using Bayesian estimation |
latin.hypercube |
Latin hypercube design matrix |
makeinputfiles |
Makes input files for condor runs of goldstein |
model |
Simple model for concept checking |
OO2002 |
Implementation of the ideas of Oakley and O'Hagan 2002 |
oo2002 |
Implementation of the ideas of Oakley and O'Hagan 2002 |
optimal.scale |
Use optimization techniques to find the optimal scales |
optimal.scales |
Use optimization techniques to find the optimal scales |
pad |
Simple pad function |
prior.B |
Prior linear fits |
prior.b |
Prior linear fits |
quad.3diag |
Evaluate a quadratic form efficiently |
quad.3form |
Evaluate a quadratic form efficiently |
quad.3form.inv |
Evaluate a quadratic form efficiently |
quad.3tdiag |
Evaluate a quadratic form efficiently |
quad.3tform |
Evaluate a quadratic form efficiently |
quad.diag |
Evaluate a quadratic form efficiently |
quad.form |
Evaluate a quadratic form efficiently |
quad.form.inv |
Evaluate a quadratic form efficiently |
quad.tdiag |
Evaluate a quadratic form efficiently |
quad.tform |
Evaluate a quadratic form efficiently |
quad.tform.inv |
Evaluate a quadratic form efficiently |
regressor.basis |
Regressor basis function |
regressor.multi |
Regressor basis function |
results.table |
Results from 100 Goldstein runs |
s.chi |
Variance estimator |
sample.from.exp.est |
Makes input files for condor runs of goldstein |
sample.n.fit |
Sample from a Gaussian process and fit an emulator to the points |
scales.likelihood |
Likelihood of roughness parameters |
sigmahatsquared |
Estimator for sigma squared |
sigmahatsquared.A |
Estimator for sigma squared |
tcprod |
Evaluate a quadratic form efficiently |
toy |
A toy dataset |
tr |
Trace of a matrix |
var.conditional |
Implementation of the ideas of Oakley and O'Hagan 2002 |