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 X as per section 4.2
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.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)

See Also

h1.toy

Examples

data(toys)
hbar.fun.toy(theta=theta.toy, X.dist=X.dist.toy, phi=phi.toy)

[Package calibrator version 1.0-48 Index]