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Comparison of empirical and theoretical distribution functions of a random variable on the basis of a nonparametric classifier

  • Analysis and Synthesis of Signals and Images
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Optoelectronics, Instrumentation and Data Processing Aims and scope

Abstract

A possibility of using nonparametric algorithms of pattern recognition in the problem of comparing empirical and theoretical distribution functions of random variables is considered. Results of computational experiments are analyzed.

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References

  1. A. V. Lapko and V. A. Lapko, “Nonparametric Algorithms of Pattern Recognition in the Problem of Testing a Statistical Hypothesis on Identity of Two Distribution Laws of Random Variables,” Avtometriya 46(6), 47–53 (2010) [Optoelectr., Instrum. Data Process. 46 (6), 545–550 (2010).]

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Authors and Affiliations

  1. Institute of Computational Modeling, Siberian Branch, Russian Academy of Sciences, Akademgorodok 50, Building 44, Krasnoyarsk, 660036, Russia

    A. V. Lapko & V. A. Lapko

  2. Reshetnev Siberian State Aerospace University, pr. Krasnoyarskii Rabochii 31, Krasnoyarsk, 660014, Russia

    V. A. Lapko

Authors
  1. A. V. Lapko
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  2. V. A. Lapko
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Corresponding author

Correspondence to A. V. Lapko.

Additional information

Original Russian Text © A.V. Lapko, V.A. Lapko, 2012, published in Avtometriya, 2012, Vol. 48, No. 1, pp. 45–49.

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Lapko, A.V., Lapko, V.A. Comparison of empirical and theoretical distribution functions of a random variable on the basis of a nonparametric classifier. Optoelectron.Instrument.Proc. 48, 37–41 (2012). https://doi.org/10.3103/S8756699012010050

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  • DOI: https://doi.org/10.3103/S8756699012010050

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