p.eqn4.supp {calibrator} | R Documentation |
Gives the probability of psi1, given observations. Equation 4 of the supplement
p.eqn4.supp(D1, y, H1, include.prior=TRUE, lognormally.distributed, return.log, phi)
D1 |
Matrix of code run points |
y |
Vector of code outputs |
H1 |
Regression function |
include.prior |
Boolean with default TRUE meaning to
return the likelihood multiplied by the aprior probability and FALSE
meaning to return the likelihood without the prior. |
lognormally.distributed |
Boolean; see ?prob.theta for
details |
return.log |
Boolean, with default FALSE meaning to return
the probability and TRUE meaning to return the logarithm of
the probability. |
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.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) p.eqn4.supp(D1=D1.toy, y=y.toy , H1=H1.toy, lognormally.distributed=TRUE, phi=phi.toy)