# W1

##### Variance matrix for beta1hat

returns the variance-covariance matrix for the estimate of beta1hat

- Keywords
- array

##### Usage

`W1(D1, H1, det=FALSE, phi)`

##### Arguments

- D1
matrix of code points

- H1
Basis function generator

- phi
Hyperparameters

- 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(W1(...,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)
W1(D1=D1.toy, H1=H1.toy, phi=phi.toy)
# }
```

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