# prior.b: Prior linear fits In emulator: Bayesian Emulation of Computer Programs

## Description

Gives the fitted regression coefficients corresponding to the specified regression model.

## Usage

 ```1 2``` ```prior.b(H, Ainv, d, b0 = NULL, B0 = NULL) prior.B(H , Ainv , B0=NULL) ```

## Arguments

 `H` Regression basis function (eg that returned by `regressor.multi()`) `Ainv` inv(A) where A is a correlation matrix (eg that returned by `corr.matrix()`) `d` Vector of data points `b0` prior constant `B0` prior coefficients

## Author(s)

Robin K. S. Hankin

## References

• J. Oakley 2004. Estimating percentiles of uncertain computer code outputs. Applied Statistics, 53(1), pp89-93.

• J. Oakley 1999. Bayesian uncertainty analysis for complex computer codes, PhD thesis, University of Sheffield.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```# example has 10 observations on 6 dimensions. # function is just sum( (1:6)*x) where x=c(x_1, ... , x_2) data(toy) val <- toy d <- apply(val,1,function(x){sum((1:6)*x)}) #add some noise: d <- jitter(d) A <- corr.matrix(val,scales=rep(1,ncol(val))) Ainv <- solve(A) H <- regressor.multi(val) prior.b(H,Ainv,d) prior.B(H,Ainv) ```

emulator documentation built on May 17, 2018, 9:03 a.m.