Re: Fitting Experimental Data

• To: mathgroup at smc.vnet.net
• Subject: [mg116488] Re: Fitting Experimental Data
• From: "Kevin J. McCann" <Kevin.McCann at umbc.edu>
• Date: Wed, 16 Feb 2011 06:50:13 -0500 (EST)
• References: <ijdoah\$f9o\$1@smc.vnet.net>

```Some comments.

(2) The peaks (spikes) in your data are not necessarily "spurious" just
because they don't fit your expected curves. You need a very good
reason, and maybe you have that, for removing them.
(3) I think I know what you mean, but there is no such thing as an
(4) Along the lines of (3) you indicate that you need to fit your data
with a Gaussian (asymmetric?), presumably to retrieve the associated
parameters; however, by deleting the peaks, you are also eliminating
important data. Why are these peaks present at the top of the curve, but
not elsewhere?

Just a few thoughts,

Kevin

On 2/15/2011 6:33 AM, mathilde Favier wrote:
> I am in trouble in trying to do a Fit using Mathematica7.
>
> Here my problem:
>
> My instrument on which I am working is giving me data looking like a plot with two round (more Gaussian) shape but with some picks on the top of each, the figures would have shown it, but you told me that I cannot enclose any file.
>
> I am only interested in the 2 round shapes, .
>
> My goal is to do a fit of those them.
>
> First I am isolating those 2 parts (ie: Plotting them whithout the data between them.)
>
> But the problem is that the picks on the top of each round shape will disturber my
> fit so I have to remove them.So now I have removed the picks, I have just 2 kind of asymetrics Gaussians with a hall on the top of each. To describe it more properly, I would say I have the rising and falling edge of two differente asymetric Gaussian.
>
> Now I start to look for a first Fit corresponding to the first asymetric Gaussian.
>
> Here is my code:
>
> model=
> b+ a*(1/(s*\[Sqrt](2*Pi)))*
> Exp[-(x-m)^2/(2*s^2)];
>
> fit=FindFit[dataleftlowband,model,{b,a,s,m}, x, MaxIterations->100]
>
> modelfit = Table[Evaluate[model/.fit],{x,1,Length[dataleftlowband]}];
>
> tmodelfit = Transpose[{xdataleftlowband,modelfit}];
>
> My big problem is that I removed some data
> in the middle of my curve and I want that according to the values kept, the
> fitting find out which should be the missing values, because I need to
> approximately trace the top of my Gaussian shape.
>
> I've tried a lot of stuff to find out how
> to solve that as, random points in the Gap...
>
> Is there a method like considering the
> first part as the rising edge and the second as the falling edge of a Gaussian?
>
> Is Mathematica able to solve that?
>
> I hope that my problem is clearly explained. It's not that easy without any pictures to show how my data look like.
>
> Tell me if you have any idea to find a solution.
>