| W2 {calibrator} | R Documentation |
Variance matrix for beta2 as per page 4 of the supplement
W2(D2, H2, V, det=FALSE)
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 |
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().
Robin K. S. Hankin
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.shef.ac.uk/~st1ao/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)
data(toys) W2(D2=D2.toy, H2=H2.toy, V=V.toy)