# etahat

0th

Percentile

##### Expectation of computer output

Returns the apostiori expectation of the computer program at a particular point with a particular set of parameters, given the code output.

Keywords
array
##### Usage
etahat(D1, D2, H1, y, E.theta, extractor, phi)
##### Arguments
D1

Matrix of code observation points and parameters

D2

Matrix of field observation points

H1

Basis functions

y

Code observations corresponding to rows of D1

E.theta

expectation wrt theta; see details

extractor

Extractor function

theta

Parameters

phi

Hyperparameters

##### Details

Argument E.theta is officially a function that, given $x$,y returns $E_\theta\left(h_1(x,\theta)\right)$.

However, if supplied a non-function (this is tested by is.function() in the code), E.theta is interpreted as values of $\theta$ to use. Recycling is carried out by function D1.fun()

##### 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)

p.page4

• etahat
##### Examples
# NOT RUN {
data(toys)

etahat(D1=D1.toy, D2=D2.toy, H1=H1.toy, y=y.toy,
E.theta=E.theta.toy, extractor=extractor.toy, phi=phi.toy)

# Now try giving E.theta=1:3, which will be interpreted as a value for theta:
etahat(D1=D1.toy, D2=D2.toy, H1=H1.toy, y=y.toy, E.theta=1:3,
extractor=extractor.toy, phi=phi.toy)

# }

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

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