# tee

0th

Percentile

##### Auxiliary functions for equation 9 of the supplement

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()

Keywords
array
##### Usage
tee(x, theta, D1, D2, phi)
h.fun(x, theta, H1, H2, phi)
##### Arguments
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

##### Details

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())

##### 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)

Ez.eqn9.supp

• tee
• h.fun
##### Examples
# NOT RUN {
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)

# }

Documentation reproduced from package calibrator, version 1.2-8, License: GPL-2

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