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From: "Arvind Iyer" <aiyer@ict.usc.edu>
Newsgroups: comp.soft-sys.matlab
Subject: Re: Implementing smoothing splines
Date: Thu, 20 Nov 2008 16:38:01 +0000 (UTC)
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Thank you that helped.

I had a couple of follow-up questions.

You've suggested spfit and supersmoother...When is one preferred over the other? (I have data with noise of very high variance.)

Also, can the user somehow modify the number of 'pieces' in the spline fit? I ask this because, for my data, the outputs of spfit look way too much like straight lines. Is this something one lives with (I haven't used splines before) or should we alter the options to get 'curvier' splines?

Doug Schwarz <see@sig.for.address.edu> wrote in message <see-B34D00.23454718112008@news.frontiernet.net>...
> In article <gg02be$av0$1@fred.mathworks.com>,
>  "Arvind Iyer" <aiyer@ict.usc.edu> wrote:
> 
> > I need to fit smoothing splines to very noisy data.
> > 
> > I do not have the Spline Toolbox (whose 'spaps' function is recommended for 
> > such problems.)
> > 
> > How can smoothing splines be implemented with other MATLAB functions? The 
> > ordinary 'spline' function simply 'joins the dots' and does not perform 
> > smoothing. 
> > 
> > What other inbuilt function can serve a similar purpose? Are there functions 
> > which perform generalized regression without the need to specify a functional 
> > form of regression function?
> 
> 
> Perhaps spfit from the FEX would be useful.
> 
> <http://www.mathworks.com/matlabcentral/fileexchange/13812>
> 
> 
> You might find a general purpose smoothing routine helpful, also.
> 
> <http://www.mathworks.com/matlabcentral/fileexchange/17986>
> 
> -- 
> Doug Schwarz
> dmschwarz&ieee,org
> Make obvious changes to get real email address.