W2: variance matrix for beta2

In RobinHankin/calibrator: Bayesian Calibration of Complex Computer Codes

Description

Variance matrix for beta2 as per page 4 of the supplement

Usage

W2(D2, H2, V, det=FALSE)

Arguments

D2	matrix of observation points
H2	regression function
V	Overall covariance matrix
det	Boolean, with default FALSE meaning to return the matrix, and TRUE meaning to return its determinant only

Details

If only the determinant is required, setting argument det to TRUE is faster than using det(W2(...,det=FALSE)), as the former avoids an unnecessary use of solve()

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

V.fun

Examples

data(toys)
W2(D2=D2.toy, H2=H2.toy, V=V.toy) 

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