approximator v1.2-7


Monthly downloads



Bayesian Prediction of Complex Computer Codes

Performs Bayesian prediction of complex computer codes when fast approximations are available. It uses a hierarchical version of the Gaussian process, originally proposed by Kennedy and O'Hagan (2000), Biometrika 87(1):1.

Functions in approximator

Name Description
is.consistent Checks observational data for consistency with a subsets object
toyapps Toy datasets for approximator package Returns generalized distances
generate.toy.observations Er, generate toy observations Correlations between points in parameter space
basis.toy Toy basis functions Mean of Gaussian process
object Optimization of posterior likelihood of hyperparameters Estimate for beta
subset_maker Create a simple subset object Generate and test subsets
approximator-package Bayesian approximation of computer models when fast approximations are available
as.sublist Converts a level one design matrix and a subsets object into a list of design matrices, one for each level
genie Genie datasets for approximator package
Pi Kennedy's Pi notation Variance matrix
Afun Matrix of correlations between two sets of points The H matrix Toy example of a hyperparameter object creation function Hdash
No Results!

Vignettes of approximator

No Results!

Last month downloads


Type Package
License GPL-2
NeedsCompilation no
Packaged 2018-08-28 23:21:38 UTC; rhankin
Repository CRAN
Date/Publication 2018-08-29 04:24:34 UTC

Include our badge in your README