[R] best way to fit a model

[Achim Zeileis]

On Tue, 13 Sep 2005 13:24:02 -0300 Ronaldo Reis-Jr. wrote:

> Em Sex 09 Set 2005 15:25, Achim Zeileis escreveu:
> > On Fri, 9 Sep 2005 14:55:04 -0300 Ronaldo Reis-Jr. wrote:
> > > Hi,
> > >
> > > I have some data that have this behaviour:
> > > |*******
> > > |        *
> > > |          *
> > > |            *
> > > |              *
> > > |----------------
> > >
> > > What is the best and simpler way to fit this in R?
> >
> > If the changepoint is known, then this is straightforward using lm:
> >
> 
> I try this. But my doubt now is:
> 
> How to justify this kind of analysis? Why dont use any linearized or
> non linear regression to fit this? Something like a log function (I
> try but is not a good function).

The motivation usually comes from subject-matter knowledge. For example,
such changepoint models are accepted by practitioners as good proxies
for certain biological processes. If you think that the data-generating
process might contain a structural change, why not model it as such?
Z

> Thanks
> Ronaldo
> -- 
> Your reasoning is excellent -- it's only your basic assumptions that
> are wrong.
> --
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