H.fun: H function

In RobinHankin/calibrator: Bayesian Calibration of Complex Computer Codes

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)

RobinHankin/calibrator documentation built on April 27, 2021, 2:47 p.m.