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Subject: Re: Using Fit to interpolate data
Posted:
Jul 28, 2012 2:39 AM
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I like Bill Rowe's:
In[12]:= params=FindFit[fiberDataDensitiesFeierabend, a Exp[b
x], {a, b}, x]
Out[12]= {a->2.06978*10^6,b->-1.61827}
and
Plot[a Exp[b x] /. params, {x, 7, 16.5},
Epilog -> {PointSize[.02], Point[fiberDataDensitiesFeierabend]}]
Here is another alternative of the same thing.
In[]:= f = NonlinearModelFit[fiberDataDensitiesFeierabend, a Exp[b x], {a, b}, x]
Out[]:= FittedModel[2.06978x10^6 * e^(-1.61827 * x) ]
In[]:= Plot[f[x],{x,7,16.5},Epilog->{PointSize[.02],Point[fiberDataDensitiesFeierabend]}]
Out[]:= (same result)
In[]:= f["FitResiduals"]
Out[]:= {-0.0000117777,0.0474942,0.0884309,0.128468,-0.038007,0.00348739}
In[]:= f["ParameterConfidenceIntervals"]
Out[]:= {{1.11329*10^6,3.02627*10^6},{-1.68272,-1.55381}}
I really like the FitResiduals you can use with object returned by NonlinearModelFit[]. There is also EstimatedVariance, BestFit. Just saying, you might want to look into it. There is an excellent youtube video.
http://www.youtube.com/watch?v=KolZZm8If9Q
Paul McHale | Electrical Engineer, Energetics Systems | Excelitas Technologies Corp.
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