[R] Non-parametric regression
David Winsemius
dwinsemius at comcast.net
Fri Jul 9 12:21:06 CEST 2010
On Jul 9, 2010, at 4:01 AM, Ralf B wrote:
> I have two data sets, each a vector of 1000 numbers, each vector
> representing a distribution (i.e. 1000 numbers each of which
> representing a frequency at one point on a scale between 1 and 1000).
> For similfication, here an short version with only 5 points.
>
>
> a <- c(8,10,8,12,4)
> b <- c(7,11,8,10,5)
>
> Leaving the obvious discussion about causality aside fro a moment, I
> would like to see how well i can predict b from a using a regression.
You can use density estimation,. There was a recent thread that
included worked examples using MASS::kde2d and locfit::locfit for
graphical display of joint distributions.
> Since I do not know anything about the distribution type and already
> discovered non-normality I cannot use parametric regression or
> anything GLM for that matter.
>
> How should I proceed in using non-parametric regression to model
> vector a and see how well it predicts b? Perhaps you could extend the
> given lines into a short example script to give me an idea? Are there
> any other options?
>
> Best,
> Ralf
David Winsemius, MD
West Hartford, CT
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