generate.toy.observations {approximator}R Documentation

Er, generate toy observations

Description

Generates toy observations on four levels using either internal (unknown) parameters and hyperparameters, or user-supplied versions.

Usage

generate.toy.observations(D1, subsets, basis.fun, hpa = NULL, betas = NULL,
export.truth = FALSE)

Arguments

D1 Design matrix for level 1 code
subsets Subset object
basis.fun Basis function
hpa Hyperparameter object. If NULL, use the internal (true but unknown) hyperparameter object
betas Regression coefficients. If NULL, use the internal (true but unknown) regression coefficients
export.truth Boolean, with default FALSE meaning to return synthetic observations and TRUE meaning to return the actual hyperparameters and coefficients.

Author(s)

Robin K. S. Hankin

References

M. C. Kennedy and A. O'Hagan 2000. “Predicting the output from a complex computer code when fast approximations are available” Biometrika, 87(1): pp1-13

Examples

data(toyapps)
generate.toy.observations(D1=D1.toy, subsets=subsets.toy, basis.fun=basis.toy)

[Package approximator version 1.0-58 Index]