Ez.eqn7.supp

0th

Percentile

Expectation of z given y, beta2, phi

Expectation as per equation 7 on the supplement

Keywords
array
Usage
Ez.eqn7.supp(z, D1, H1, D2, H2,  extractor, beta2, y, E.theta,  phi)
Arguments
z

Vector of observations

D1

Matrix whose rows are code run points

H1

Regressor basis functions

D2

Matrix whose rows are observation points

H2

Regressor basis functions

extractor

Function to split D1

beta2

coefficients

y

Code outputs at points corresponding to rows of D1

E.theta

Expectation function to use

phi

hyperparameters

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

V.fun

Aliases
  • Ez.eqn7.supp
Examples
# NOT RUN {
data(toys)
etahat.d2 <- etahat(D1=D1.toy, D2=D2.toy, H1=H1.toy, y=y.toy,
    E.theta=E.theta.toy, extractor=extractor.toy, phi=phi.toy)
beta2 <- beta2hat.fun(D1=D1.toy, D2=D2.toy, H1=H1.toy, H2=H2.toy, V=V.toy, z=z.toy,
etahat.d2=etahat.d2, extractor=extractor.toy, E.theta=E.theta.toy,
Edash.theta=Edash.theta.toy, phi=phi.toy)
Ez.eqn7.supp(z=z.toy, 
    D1=D1.toy, H1=H1.toy, D2=D2.toy, H2=H2.toy, 
    extractor=extractor.toy, beta2=beta2, y=y.toy, 
    E.theta=E.theta.toy, 
    phi=phi.toy)
# }
Documentation reproduced from package calibrator, version 1.2-8, License: GPL-2

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