Predicted values using using local polynomials
Predicted values from a local polynomials of degree less than 2. See
locpoly for fast binned implementation
over an equally-spaced grid of local polynomial (gaussian kernel only)
Missing values are not allowed.
## S3 method for class 'npregress'
predict(object, newdata, interval=
c("none", "confidence", "prediction"), deriv=FALSE, ...)object |
Object of class |
newdata |
An optional vector of values to be predicted. If omitted, the fitted values are used. |
interval |
Type of interval calculation. Only |
deriv |
Bolean. If |
... |
Further arguments passed to or from other methods. |
Produces a vector of predictions. If deriv
is TRUE the value is a named list with components: yhat
which contains predictions and (if relevant) deriv the
first derivative of the local polynomial of degree 1.
Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.
Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.
f <- function(x){sin(5*pi*x)}
n <- 100
x <- runif(n)
z <- f(x)
sigma2 <- 0.05*var(z)
erreur<-rnorm(n,0,sqrt(sigma2))
y<-z+erreur
grid <- seq(min(x),max(x),length=500)
res <- npregress(x,y,bandwidth=0.02,control.par=list(degree=1))
plot(x,y)
lines(grid,predict(res,grid))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.