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https://issues.apache.org/jira/browse/MATH-372?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=12877530#action_12877530
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Matt Price edited comment on MATH-372 at 6/10/10 2:56 PM:
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A quick update...
I've successfully gotten linear and non-linear regression working via Apache
Commons Math for linear, point-to-point, log-log, 4PL and 5PL regression
models. The troubles I had were due to errors in complex derivatives. My aim
is to replace software that is currently using a commercial product (DataFitX).
From what I can tell, Apache Commons Math is faster and more accurate than
DataFitX. Good job Apache :)
P.S. Wolfram Alpha is a great website for solving your regression model's
derivatives (www.wolframalpha.com)
was (Author: mprice):
A quick update...
I've successfully gotten linear and non-linear regression working via Apache
Commons Math for linear, point-to-point, log-log, 4PL and 5PL regression
models. The troubles I had were due to errors in complex derivatives. My aim
is to replace software that is currently using a commercial product (DataFitX).
From what I can tell, Apache Commons Math is faster and more accurate that
DataFitX. Good job Apache :)
P.S. Wolfram Alpha is a great website for solving your regression model's
derivatives (www.wolframalpha.com)
> Curve fitting appears unreliable
> --------------------------------
>
> Key: MATH-372
> URL: https://issues.apache.org/jira/browse/MATH-372
> Project: Commons Math
> Issue Type: Bug
> Affects Versions: 2.1
> Environment: Win7 x64, Netbeans, JDK 1.6.0.18
> Reporter: Matt Price
> Attachments: CurveFitterDebug.java, CurveFitting.ods
>
> Original Estimate: 8h
> Remaining Estimate: 8h
>
> I've been trying to find a good curve fitting library for Java for the last
> couple of weeks. I came across Apache Commons Math and was really excited
> because I like all things Apache. The curve fitting API looks good and is
> fairly easy to use, however, it doesn't seem to be as accurate as it
> should/could be.
> I've produced some code and data that shows that the initial parameter
> guesses affect the results too much. Guess low and the curve ends up low,
> guess high and the curve ends up high. I wish I had a stronger
> statistics/math background to make more sense of this. I've tried playing
> with the optimizer's options (costRelativeToTolerance,
> initialStepBoundFactor, maxEvaluations, maxIterations, orthTolerance and
> parRelativeTolerance) but nothing seems to improve the end result.
> I've attached the spreadsheet and Java code. FYI, in the spreadsheet you'll
> see an entry in the chart for DataFitX. It is a COM library used in my
> company's current software that needs to be replaced.
> Any help on this would be greatly appreciated. If you need more info, let me
> know and I'll supply it as quickly as I can.
> Thanks,
> Matt
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