tee {calibrator} | R Documentation |
Returns a vector whose elements are the “distances” from a point
to the observations and code run points (tee()
); and basis
functions for use in Ez.eqn9.supp()
.
tee(x, theta, D1, D2, phi) h.fun(x, theta, H1, H2, phi)
x |
Point from which distances are calculated |
theta |
Value of parameters |
D1,D2 |
Design matrices of code run points and field observation
points respectively (tee() ) |
H1,H2 |
Basis functions for eta and model inadequacy term
respectively (h.fun() ) |
phi |
Hyperparameters |
Equation 9 of the supplement is identical to equation 10 of KOH2001.
Function h.fun()
returns the first of the subsidiary equations
in equation 9 of the supplement and function tee()
returns the
second (NB: do not confuse this with functions t1bar()
and
t2bar()
which are internal to EK.eqn10.supp()
).
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) tee(x=x.toy, theta=theta.toy, D1=D1.toy, D2=D2.toy, phi=phi.toy) # Now some vectorized examples: jj <- rbind(x.toy , x.toy , x.toy+0.01,x.toy+1,x.toy*10) tee(x=jj, theta=theta.toy, D1=D1.toy, D2=D2.toy, phi=phi.toy) h.fun(x=jj, theta=theta.toy, H1=H1.toy, H2=H2.toy, phi=phi.toy)