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Nonparametric algorithms of pattern recognition in the problem of testing a statistical hypothesis on identity of two distribution laws of random variables

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

Abstract

The possibility of using nonparametric algorithms of pattern recognition for testing hypotheses on distributions of random variables is discussed. Results of computational experiments are compared with the Kolmogorov-Smirnov criterion.

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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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Correspondence to A. V. Lapko.

Additional information

Original Russian Text © A.V. Lapko, V.A. Lapko, 2010, published in Avtometriya, 2010, Vol. 46, No. 6, pp. 47–53.

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Lapko, A.V., Lapko, V.A. Nonparametric algorithms of pattern recognition in the problem of testing a statistical hypothesis on identity of two distribution laws of random variables. Optoelectron.Instrument.Proc. 46, 545–550 (2010). https://doi.org/10.3103/S8756699011060069

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  • DOI: https://doi.org/10.3103/S8756699011060069

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