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)