etahat {calibrator} | R Documentation |
Returns the apostiori expectation of the computer program at a particular point with a particular set of parameters, given the code output.
etahat(D1, D2, H1, y, E.theta, extractor, phi)
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 |
Argument E.theta
is officially a function that, given
x,y returns
E_theta(h1(x,theta)).
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()
.
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) 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)