Subject: Re: Using Fit to interpolate data
- To: mathgroup at smc.vnet.net
- Subject: [mg127475] Subject: Re: Using Fit to interpolate data
- From: "McHale, Paul" <Paul.McHale at excelitas.com>
- Date: Sat, 28 Jul 2012 02:38:19 -0400 (EDT)
- Delivered-to: l-mathgroup@mail-archive0.wolfram.com
- Delivered-to: l-mathgroup@wolfram.com
- Delivered-to: mathgroup-newout@smc.vnet.net
- Delivered-to: mathgroup-newsend@smc.vnet.net
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.
=09
Phone: +1 937.865.3004 | Fax: +1 937.865.5170 | Mobile: +1 937.371.2828
1100 Vanguard Blvd, Miamisburg, Ohio 45342-0312 USA
Paul.McHale at Excelitas.com
www.excelitas.com
Please consider the environment before printing this e-mail.
This email message and any attachments are confidential and proprietary to Excelitas Technologies Corp. If you are not the intended recipient of this message, please inform the sender by replying to this email or sending a message to the sender and destroy the message and any attachments.
Thank you