plotCGP {CGP} R Documentation

## Jackknife (leave-one-out) actual by predicted diagnostic plot

### Description

Draw jackknife (leave-one-out) actual by predicted plot to measure goodness-of-fit.

### Usage

plotCGP(object)


### Arguments

 object An object of class "CGP"

### Details

Draw the actual observed values on the y-axis and the jackknife (leave-one-out) predicted values on the x-axis. The goodness-of-fit can be measured by how well the points lie along the 45 degree diagonal line.

### Value

This function draws the jackknife (leave-one-out) actual by predicted plot.

### Author(s)

Shan Ba <shanbatr@gmail.com> and V. Roshan Joseph <roshan@isye.gatech.edu>

### References

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

CGP

### Examples

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<-x1^2+x2^2
## Not run:
#The CGP model
mod<-CGP(X,yobs,nugget_l=0.001)
plotCGP(mod)

## End(Not run)


[Package CGP version 2.1-1 Index]