# print.CGP: CGP model summary information In CGP: Composite Gaussian Process Models

## Description

Print a brief summary of a “`CGP`” object.

## Usage

 ```1 2``` ```## S3 method for class 'CGP' print(x, ...) ```

## Arguments

 `x` An object of class "`CGP`" `...` For compatibility with generic method `print`

## Details

This function prints a brief summary of a “`CGP`” object.

## Value

This function prints the results of:

 `lambda` Estimated nugget value (λ) `theta` Estimated correlation parameters (θ) in the global GP `alpha` Estimated correlation parameters (α) in the local GP `bandwidth` Estimated bandwidth parameter (b) in the variance model

## Author(s)

Shan Ba <[email protected]> and V. Roshan Joseph <[email protected]>

## References

Ba, S. and V. Roshan Joseph (2012) “Composite Gaussian Process Models for Emulating Expensive Functions”. Annals of Applied Statistics, 6, 1838-1860.

`CGP`, `summary.CGP`, `predict.CGP`

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12``` ```x1<-c(0,.02,.075,.08,.14,.15,.155,.156,.18,.22,.29,.32,.36, .37,.42,.5,.57,.63,.72,.785,.8,.84,.925,1) x2<-c(.29,.02,.12,.58,.38,.87,.01,.12,.22,.08,.34,.185,.64, .02,.93,.15,.42,.71,1,0,.21,.5,.785,.21) X<-cbind(x1,x2) yobs<-sin(1/((x1*0.7+0.3)*(x2*0.7+0.3))) ## Not run: #Fit the CGP model mod<-CGP(X,yobs) print(mod) ## End(Not run) ```

### Example output

```There were 50 or more warnings (use warnings() to see the first 50)
Call:
CGP.default(X = X, yobs = yobs)

Lambda:
[1] 0.6210288

Theta:
x1     x2
[1,] 6.065496 8.0934

Alpha:
x1       x2
[1,] 143.177 145.2049

Bandwidth:
[1] 1
```

CGP documentation built on June 12, 2018, 5:19 p.m.