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Re: Smooth line approximating minima of a data series

From: Olaf Till
Subject: Re: Smooth line approximating minima of a data series
Date: Wed, 24 Feb 2010 11:23:06 +0100
User-agent: Mutt/1.5.18 (2008-05-17)

On Wed, Feb 24, 2010 at 09:04:07AM +0100, Matthias Brennwald wrote:
> Dear all
> Consider a series of data values that reflect a smooth function (e.g.  
> a low-degree polynomial), but there might be additional features in  
> the data (e.g. narrow peaks or noise). I'd like to fit a polynomial to  
> this data, whereby this polynomial reflects a smooth approximation of  
> the minima of the raw data (I call this the "base line"). The  
> following might help to illustrate what I'm trying to accomplish:
>      x = [-1:0.01:1]; % x-axis values
>      p = [-3 2 1 0]; yp = polyval (p,x); % make up a polynomial  
> reflecting the "base line" for illustration
>      y = yp + rand(size(x)); % this would be the raw data
>      plot (x,y,x,yp); legend ('raw data','base line') % plot the raw  
> data and the polynomial for illustration
> Has anyone an idea of how to accomplish this? Are there standard  
> methods?

What about polyfit?


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