summary.npregress: Summarizing local polynomial fits

In ibr: Iterative Bias Reduction

Summarizing local polynomial fits

Description

summary method for class “npregress”.

Usage

## S3 method for class 'npregress'
summary(object,  criteria="call", ...)

Arguments

object	Object of class npregress.
criteria	Character string which gives the criteria evaluated for the model. The criteria available are GCV (default, "gcv"), AIC ("aic"), corrected AIC ("aicc"), BIC ("bic") or gMDL ("gmdl"). The string "call" return the criterion used in the call of npregress.
...	Further arguments passed to or from other methods.

Value

The function summary.npregress computes and returns a list of summary statistics of the local polynomial smoother given in object

Author(s)

Pierre-Andre Cornillon, Nicolas Hengartner and Eric Matzner-Lober.

References

Wand, M. P. and Jones, M. C. (1995). Kernel Smoothing. Chapman and Hall, London.

See Also

npregress, summary.npregress

Examples

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
res <- npregress(x,y,bandwidth=0.02)
summary(res)

ibr documentation built on Sept. 13, 2023, 5:08 p.m.