# W2

##### variance matrix for beta2

Variance matrix for beta2 as per page 4 of the supplement

- Keywords
- array

##### Usage

`W2(D2, H2, V, det=FALSE)`

##### Arguments

- D2
matrix of observation points

- H2
regression function

- V
Overall covariance matrix

- det
Boolean, with default

`FALSE`

meaning to return the matrix, and`TRUE`

meaning to return its determinant only

##### Details

If only the determinant is required, setting argument `det`

to
`TRUE`

is faster than using `det(W2(...,det=FALSE))`

, as the
former avoids an unnecessary use of `solve()`

##### 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)
W2(D2=D2.toy, H2=H2.toy, V=V.toy)
# }
```

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