predict.nnreg(out, x, model=NA, derivative=0, type="full")
out
| Fitted nnreg object. |
x
| Matrix of x values on which to evaluate the neural net surface. |
model
| Model number to use in predicting. Default is the best model based on GCV(2). |
derivative
| Derivative of function is returned if derivative=1. |
type
|
Form of predictions. Default is the prediction for the independent
variable. If type="terms" the individual values for the hidden units
are calculated.
|
nnreg(ozone$x,ozone$y,1,2) -> fit # nnreg fit cbind(seq(87,89,,10),seq(40,42,,10)) -> x # new x matrix predict(fit,x) -> out # evaluate fit at x