hbar.fun.toy {calibrator} | R Documentation |
Toy example of hbar (section 4.2)
Description
A toy example of the expectation of h as per section 4.2
Usage
hbar.fun.toy(theta, X.dist, phi)
Arguments
theta |
Parameter set |
X.dist |
Distribution of variable inputs |
phi |
Hyperparameters |
Details
Note that if h1.toy()
or h2.toy()
change, then
hbar.fun.toy()
will have to change too; see ?h1.toy
for an
example in which nonlinearity changes the form of E.theta.toy()
Value
Returns a vector as per section 4.2 of KOH2001S
Author(s)
Robin K. S. Hankin
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)
See Also
Examples
data(toys)
hbar.fun.toy(theta=theta.toy, X.dist=X.dist.toy, phi=phi.toy)