Description Usage Arguments Value Note References See Also Examples
Creates new toy datasets, by sampling from an explicitly specified multivariate Gaussian distribution whose covariance matrix is that required for a Gaussian process.
1 | create.new.toy.datasets(D1,D2,export=FALSE)
|
export |
Boolean, with default |
D1 |
D1; set of code run points |
D2 |
D2; set of field observation points |
Returns a list of three elements:
y.toy |
|
z.toy |
|
d.toy |
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
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)
toys
, reality
, latin.hypercube
1 2 | data(toys)
create.new.toy.datasets(D1=D1.toy , D2=D2.toy)
|
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