H.fun {calibrator}

H function

Description

H. See front page of KOHsupp.

Usage

H.fun(theta, D1, D2, H1, H2, phi)

Arguments

theta

parameters

D1

matrix of code run points

D2

matrix of observation points

H1

Regressor function for D1

H2

Regressor function for D2

phi

hyperparameters

Author(s)

Robin K. S. Hankin

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)

Examples

data(toys)
H.fun(theta=theta.toy, D1=D1.toy, D2=D2.toy, H1=H1.toy,
       H2=H2.toy, phi=phi.toy)

H.fun(theta=theta.toy, D1=D1.toy[1,,drop=FALSE], D2=D2.toy,
       H1=H1.toy, H2=H2.toy, phi=phi.toy)

H.fun(theta=theta.toy, D1=D1.toy[1,,drop=FALSE],
       D2=D2.toy[1,,drop=FALSE],
       H1=H1.toy, H2=H2.toy, phi=phi.toy)