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
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.shef.ac.uk/~st1ao/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)