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The best polynomial multidimensional-matrix regression

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Cybernetics and Systems Analysis Aims and scope

Abstract

The problem of finding the best polynomial multidimensional-matrix regression is formulated. A system of equations is obtained to calculate the parameters of polynomial regression of any degree. Expressions for the parameters of constant linear and square regressions are derived as well.

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References

  1. N. P. Sokolov, An Introduction to the Theory of Multidimensional Matrices [in Russian], Naukova Dumka, Kyiv (1972).

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  2. V. S. Mukha, Analysis of Multidimensional Data: A Monograph [in Russian], Tekhnoprint, Minsk (2004).

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  3. N. V. Smirnov and I. V. Dunin-Barkovskii, A Course of Probability Theory and Mathematical Statistics for Engineering Applications [in Russian], Nauka, Moscow (1969).

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  4. V. S. Mukha, “Differentiating functions of symmetric multidimensional matrices,” Izv. NAN Belarusi, Ser. Fiz.-Mat. Nauk, No. 1, 56–61 (2005).

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Authors and Affiliations

  1. Belarusian State University of Information Sciences and Radio Electronics, Minsk, Belarus

    V. S. Mukha

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  1. V. S. Mukha
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Translated from Kibernetika i Sistemnyi Analiz, No. 3, pp. 138–143, May–June 2007.

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Mukha, V.S. The best polynomial multidimensional-matrix regression. Cybern Syst Anal 43, 427–432 (2007). https://doi.org/10.1007/s10559-007-0065-3

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  • DOI: https://doi.org/10.1007/s10559-007-0065-3

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