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Linear Regression and Curve Fitting

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Numeric Computation and Statistical Data Analysis on the Java Platform

Part of the book series: Advanced Information and Knowledge Processing ((AI&KP))

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Abstract

Interpretation of empirical data using mathematical equations or functions is a widely used technique to describe data, explain relationships between variables, or compare data with theoretical expectations. Such an approach is also used for forecasting of future trends.

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Notes

  1. 1.

    Note that, for a small number of events, the binning can result in a loss of information and large statistical uncertainties for the parameter estimates [1]. On the other hand, a benefit of the binning is that it allows for the goodness-of-fit test.

References

  1. Eidelman S et al (2004) Review of particle physics. Phys Lett B 592:1

    Article  Google Scholar 

  2. FreeHep, Jas, Java analysis studio. http://jas.freehep.org/jas3/

  3. Donszelmann M, Johnson T, Serbo V, Turri M (2008) JAIDA, JAS3, WIRED4 and the AIDA tag library: experience and new developments. J Phys Conf Ser 119:032016

    Google Scholar 

  4. Lutus P, Polynomial Regression Data Fit. Java version. http://www.arachnoid.com/polysolve/

  5. FreeHEP Java Libraries. http://java.freehep.org/

  6. Fitzgibbon AW, Pilu M, Fisher RB (1999) Direct least-squares fitting of ellipses. IEEE Trans Pattern Anal Mach Intell 21:476

    Article  Google Scholar 

  7. Koza J (1992) Genetic programming: on the programming of computers by means of natural selection (complex adaptive systems). Massachusetts IT, USA

    MATH  Google Scholar 

  8. Lagodiuk Y, Genetic-programming Java package. https://github.com/lagodiuk/genetic-algorithm

  9. JGap, Java genetic algorithms package. http://jgap.sourceforge.net/

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Authors and Affiliations

  1. HEP Division, Argonne National Laboratory, Lemont, IL, USA

    Sergei V. Chekanov

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  1. Sergei V. Chekanov
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Correspondence to Sergei V. Chekanov .

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© 2016 Springer International Publishing Switzerland

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Chekanov, S.V. (2016). Linear Regression and Curve Fitting. In: Numeric Computation and Statistical Data Analysis on the Java Platform. Advanced Information and Knowledge Processing. Springer, Cham. https://doi.org/10.1007/978-3-319-28531-3_11

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  • DOI: https://doi.org/10.1007/978-3-319-28531-3_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-28529-0

  • Online ISBN: 978-3-319-28531-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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