predict.ENNreg {evreg} | R Documentation |
Prediction method for the ENNreg model
Description
Predicted values based on a trained ENNreg model (object of class "ENNreg").
Usage
## S3 method for class 'ENNreg'
predict(object, newdata, yt = NULL, ...)
Arguments
object |
An object of type "ENNreg" |
newdata |
Input matrix of attributes for test data |
yt |
Optional test response vector |
... |
Further arguments passed to or from other methods |
Value
Predictions for the new data, coded as a list with the following components:
- mux
Predicted means
- sigx
Predicted standard deviations.
- hx
Prediction precisions.
- Einf
Lower expectation.
- Esup
Upper expectations
- NLL
Negative log likelihood (computed only if yt is provided).
- RMS
Root mean squared error (computed only if yt is provided).
See Also
Examples
# Boston dataset
library(MASS)
X<-as.matrix(scale(Boston[,1:13]))
y<-Boston[,14]
set.seed(220322)
n<-nrow(Boston)
ntrain<-round(0.7*n)
train <-sample(n,ntrain)
fit <- ENNreg(X[train,],y[train],K=30)
pred<-predict(fit,newdata=X[-train,],yt=y[-train])
plot(y[-train],pred$mux,xlab="observed response",ylab="predicted response")
[Package evreg version 1.1.1 Index]