cov.p5.supp {calibrator}R Documentation

Covariance function for posterior distribution of z

Description

Covariance function for posterior distribution of z(.) conditional on estimated hyperparameters and calibration parameters theta.

Usage

cov.p5.supp(x, xdash, theta, d, D1, D2, H1, H2, phi)

Arguments

x first point, or a matrix whose rows are the points of interest
xdash second point, or a matrix whose rows are the points of interest
theta Parameters
d Observed values
D1 Code run design matrix
D2 Observation points of real process
H1 Basis function for D1
H2 Basis function for D2
phi Hyperparameters

Details

Evaluates the covariance function: the last formula on page 5 of the supplement

Value

Returns a matrix of covariances

Note

May return the transpose of the desired object

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)

Examples

data(toys)
x <- rbind(x.toy,x.toy+1,x.toy,x.toy,x.toy)
rownames(x) <- letters[1:5]
xdash <- rbind(x*2,x.toy)
rownames(xdash) <- LETTERS[1:6]

cov.p5.supp(x=x,xdash=xdash,theta=theta.toy,d=d.toy,D1=D1.toy,D2=D2.toy,H1=H1.toy,H2=H2.toy,phi=phi.toy)

phi.true <- phi.true.toy(phi=phi.toy)
cov.p5.supp(x=x,xdash=xdash,theta=theta.toy,d=d.toy,D1=D1.toy,D2=D2.toy,H1=H1.toy,H2=H2.toy,phi=phi.true)

[Package calibrator version 1.0-28 Index]