create.new.toy.datasets {calibrator}

Create new toy datasets

Description

Creates new toy datasets, by sampling from an explicitly specified multivariate Gaussian distribution whose covariance matrix is that required for a Gaussian process.

Usage

create.new.toy.datasets(D1,D2,export=FALSE)

Arguments

export

Boolean, with default FALSE meaning to return toy datasets and TRUE meaning to return, instead, a list of the true values of the parameters

D1

D1; set of code run points

D2

D2; set of field observation points

Value

Returns a list of three elements:

y.toy

z.toy

d.toy

Note

Because function create.new.toy.datasets() calls computer.model() and model.inadequacy(), the datasets returned are drawn from a multivariate Gaussian distribution which is a Gaussian process

References

• M. C. Kennedy and A. O'Hagan 2001. Bayesian calibration of computer models. Journal of the Royal Statistical Society B, 63(3) pp425-464

• M. C. Kennedy and A. O'Hagan 2001. Supplementary details on Bayesian calibration of computer models, Internal report, University of Sheffield. Available at http://www.tonyohagan.co.uk/academic/ps/calsup.ps

• R. K. S. Hankin 2005. Introducing BACCO, an R bundle for Bayesian analysis of computer code output, Journal of Statistical Software, 14(16)

See Also

toys, reality, latin.hypercube

Examples

data(toys)
create.new.toy.datasets(D1=D1.toy , D2=D2.toy)