Description Usage Arguments Author(s) References See Also Examples
Function to determine a postiori probability of hyperparameters rho, lambda and psi2, given observations and psi1.
1 2 |
D1 |
Matrix of code run points |
D2 |
Matrix of observation points |
H1 |
Basis function (vectorized) |
H2 |
Regression function for D2 |
V |
Covariance matrix; default value of |
y |
Vector of code outputs |
z |
Vector of observation values |
E.theta |
Expectation over theta |
Edash.theta |
Expectation over theta WRT E' |
extractor |
Function to extract independent variables and parameters from D1 |
include.prior |
Boolean, with |
lognormally.distributed |
Boolean with |
return.log |
Boolean, with default |
phi |
Hyperparameters |
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.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)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | data(toys)
p.page4(D1=D1.toy, D2=D2.toy, H1=H1.toy, H2=H2.toy, V=NULL, y=y.toy,
z=z.toy,E.theta=E.theta.toy, Edash.theta=Edash.theta.toy, extractor=extractor.toy, phi=phi.toy)
## Now compare the above value with p.page4() calculated with phi
## differing only in psi2:
phi.toy.new <- phi.change(phi.fun=phi.fun.toy, old.phi = phi.toy, psi2=c(8,8,8))
p.page4(D1=D1.toy, D2=D2.toy, H1=H1.toy, H2=H2.toy, V=V.toy, y=y.toy, z=z.toy,
E.theta=E.theta.toy, Edash.theta=Edash.theta.toy,
extractor=extractor.toy, phi=phi.toy.new)
## different!
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