ksmooth {stats}  R Documentation 
Kernel Regression Smoother
Description
The Nadaraya–Watson kernel regression estimate.
Usage
ksmooth(x, y, kernel = c("box", "normal"), bandwidth = 0.5,
range.x = range(x),
n.points = max(100L, length(x)), x.points)
Arguments
x 
input x values. Long vectors are supported. 
y 
input y values. Long vectors are supported. 
kernel 
the kernel to be used. Can be abbreviated. 
bandwidth 
the bandwidth. The kernels are scaled so that their
quartiles (viewed as probability densities) are at

range.x 
the range of points to be covered in the output. 
n.points 
the number of points at which to evaluate the fit. 
x.points 
points at which to evaluate the smoothed fit. If
missing, 
Value
A list with components
x 
values at which the smoothed fit is evaluated. Guaranteed to be in increasing order. 
y 
fitted values corresponding to 
Note
This function was implemented for compatibility with S, although it is nowhere near as slow as the S function. Better kernel smoothers are available in other packages such as KernSmooth.
Examples
require(graphics)
with(cars, {
plot(speed, dist)
lines(ksmooth(speed, dist, "normal", bandwidth = 2), col = 2)
lines(ksmooth(speed, dist, "normal", bandwidth = 5), col = 3)
})