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From: TideMan <mulgor@gmail.com>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Fitting a cdf to noisy data
Date: Wed, 18 Mar 2009 12:13:34 -0700 (PDT)
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On Mar 19, 7:09=A0am, "Katya Frois-Moniz" <kmo...@mit.edu> wrote:
> Thanks for you post, Peter!
>
> > =A0From your description, it's not clear to me whether you want to fit =
a curve to observations of concentration vs. time, or if you want to fit a =
normal distribution to observed times. =A0
>
> I'm really looking to fit a curve (normal cdf) to concentration vs. time,=
 and obtain the parameters.
>
> >It's also not clear to me if the concentrations you have are cumulative,=
 or if they include both "births" and "deaths" if you see what I mean.
>
> Technically, they include deaths, but these are assumed to be negligible,=
 so the concentration is (essentially) cumulative.
>
>
>
> > You may want to use the Curve Fitting Toolbox. =A0You may want to use N=
ORMFIT in the Statistics Toolbox. =A0You may want to fit a "discrete normal=
" using MLE in the statistics Toolbox.
>
> I think I'll try cftool again, and see if I can get help setting up the c=
ustom equation, since what I tried before didn't work.
>
> Thanks !

I don't completely understand your problem, but the way I generate a
CDF from data is to first calculate the histogram (the empirical PDF),
then integrate to give the CDF.  This gives the probability that the
data exceed a particular value.

You say
>I tried generating the pdf by plotting the *incremental* values (i.e. y(t)=
 - y(t-1)) vs time

Well, that's not a PDF as I know it.  It's simply a gradient vs time.