# Vd

From calibrator v1.2-8
by Robin K S Hankin

##### Variance matrix for d

Variance matrix for d, as per the bottom of page 1 of the supplement

- Keywords
- array

##### Usage

`Vd(D1, D2, theta, phi)`

##### Arguments

- D1
matrix of code run points

- D2
matrix of observation points

- theta
Parameters

- 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) pp425-464M. 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.psR. K. S. Hankin 2005.

*Introducing BACCO, an R bundle for Bayesian analysis of computer code output*, Journal of Statistical Software, 14(16)

##### See Also

##### Examples

```
# NOT RUN {
data(toys)
Vd(D1=D1.toy, D2=D2.toy, theta=theta.toy, phi=phi.toy)
# }
```

*Documentation reproduced from package calibrator, version 1.2-8, License: GPL-2*

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