Vd: Variance matrix for d

In RobinHankin/calibrator: Bayesian Calibration of Complex Computer Codes

Description

Variance matrix for d, as per the bottom of page 1 of the supplement

Usage

Vd(D1, D2, theta, phi)

Arguments

D1	matrix of code run points
D2	matrix of observation points
theta	Parameters
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)

See Also

H.fun,V1,V2,C1

Examples

data(toys)
Vd(D1=D1.toy, D2=D2.toy, theta=theta.toy, phi=phi.toy)

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