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st: RE: Constrained Lowess

From   "Nick Cox" <[email protected]>
To   <[email protected]>
Subject   st: RE: Constrained Lowess
Date   Fri, 2 May 2008 11:47:34 +0100

Quite how to get useful results from smoothing a binary response is not
clear to me. 

If the data were proportions on (0,1) or even [0,1] I would suggest 
some kind of transformation approach. -lowess, logit- is presumably
intended to help. 
Otherwise consider something like an angular or folded root
transformation, applying -lowess- and then transforming back. 

But for binary data any transformation just maps two distinct values to
two other distinct values and so cannot help, so far as I can see. 

In the case of unemployment data, presumably you are dealing with
individuals? If they are aggregate data for lots of individuals I would
collapse by age to get proportion of unemployed, and then smooth if
necessary. It sounds as if you want something quite different, however.
Also, as you regard -age- as categorical I probably don't understand
what you are trying to do. 

[email protected] 

Sergiy Radyakin

I am plotting a smoothed graph (-lowess-) of a binary variable (e.g.
unemployed) by categorical (e.g. age). However the smoothed values are
not necessarily in the [0;1] range, where unemployment must be by
definition. I can save the smoothed values into a new variable with
the option -generate(newvar)- and then truncate the negatives and
values larger than one, but I believe smoothing must look differently
if I could tell -lowess- to look for such a constrained value in the
first place. As it follows from the description of -lowess- it doesn't
have such a feature. Is there any user-written command or simple
algorithm for this purpose?

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