Bayesian Prediction of Complex Computer Codes
Matrix of correlations between two sets of points
Bayesian approximation of computer models when fast approximations are...
Converts a level one design matrix and a subsets object into a list of...
Toy basis functions
Estimate for beta
Correlations between points in parameter space
Er, generate toy observations
The H matrix
Hdash
Toy example of a hyperparameter object creation function
Checks observational data for consistency with a subsets object
Mean of Gaussian process
Optimization of posterior likelihood of hyperparameters
Kennedy's Pi notation
Create a simple subset object
Generate and test subsets
Returns generalized distances
Variance matrix
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.