[R] FW: Kernel smoothing with bandwidth which varies with x

[IOANNA]

Hello all,

I would like to use the Nadaraya-Watson estimator assuming a Gaussian
kernel: So far I sued the
library(sm)
library(sm)
x<-runif(5000)
y<-rnorm(5000)
plot(x,y,col='black')
h1<-h.select(x,y,method='aicc')
lines(ksmooth(x,y,bandwidth=h1))

which works fine. What if my data were clustered requiring a bandwidth that
varies with x? How can I do that?

Thanks in advance,
Ioanna

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[Uwe Ligges]

On 23.05.2013 18:10, IOANNA wrote:
> Hello all,
>
> I would like to use the Nadaraya-Watson estimator assuming a Gaussian
> kernel: So far I sued the
> library(sm)
> library(sm)
> x<-runif(5000)
> y<-rnorm(5000)
> plot(x,y,col='black')
> h1<-h.select(x,y,method='aicc')
> lines(ksmooth(x,y,bandwidth=h1))
>
> which works fine. What if my data were clustered requiring a bandwidth that
> varies with x? How can I do that?

I'd start with trying to transform x so that the bandwidth can be fixed.

Uwe Ligges