Hello,
if you have a lot of data points (say more than two thousands), a
parametric model can not caputre the structure of the data very well,
or better, there is loss of information.
There a plenty of semi and non-parametric regression models out there.
Take a look at www.md-tech.com
for software and literature.
However it is only useful for large data sets and sometimes very
difficult to interpret.
best regards
stefan

Rajarshi Guha <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>...
> Hi,
>   I've come across kernel density estimation technques and I was wonderin 
> what can they be used for? It appears to me that they just give a
> representation of the PDF for the given data. But can these technique be
> used for other purposes?
> 
> Another related question is that I have seen some examples of 1D and 2D
> KDE technqiues - is it possible (or rather available) to have nD KDE
> techniques?
> 
> I'd appreciate it if anybody could point some introductory texts in this
> area ?
> 
> Thanks,
> Rajarshi
.
.
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