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Numerical method of estimating the maximal likelihood of a smooth parametric manifold

  • Stochastic Systems, Queueing Systems
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Abstract

Consideration was given to the numerical estimation of the maximum likelihood for the parameter vector describing a smooth manifold. Estimation is based on the results of observing motion of a dynamic plant whose trajectory belongs to this manifold and is measured with random errors having normal distribution with certain parameters. Application of the maximum likelihood method to such problems gives rise to the problem of nonlinear highdimensionality programming. Some constructive analytical results obtained enable significant reduction in the problem dimensionality. The problem of identifying the plane of motion of a dynamic plant was examined.

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References

  1. Cramer, H., Mathematical Methods of Statistics, Princeton: Princeton Univ. Press, 1937. Translated under the title Matematicheskie metody statistiki, Moscow: Mir, 1975.

    MATH  Google Scholar 

  2. Zacks, Sh., The Theory of Statistical Interference, New York: Wiley, 1971. Translated under the title Teoriya statisticheskikh vyvodov, Moscow: Mir, 1975.

    Google Scholar 

  3. Tortrat, A. and Hennequin, P.-L., Theorie des probabilités et quelques applications, Paris: Masson et Cie (Laval, impr. Barneoud), 1965. Translated under the title Teoriya veroyatnostei i nekotorye ee prilozheniya, Moscow: Nauka, 1974.

    MATH  Google Scholar 

  4. Bard, Y., Nonlinear Parameter Estimation, New York: Academic, 1974. Translated under the title Nelineinoe otsenivanie parametrov, Moscow: Statistika, 1979.

    MATH  Google Scholar 

  5. Demidenko, E.Z., Lineinaya i nelineinaya regressii (Linear and Nonlinear Regressions), Moscow: Finansy i Statistika, 1981.

    Google Scholar 

  6. Repin, V.G. and Tartakovskii, G.P., Statisticheskii sintez pri apriornoi neopredelennosti i adaptatsiya informatsionnykh system (Statistical Design under A-Priori Uncertainty and Adaptation of Information Systems), Moscow: Sovetskoe Radio, 1977.

    Google Scholar 

  7. Polyak, B.T., Method of Newton and Its Role in Optimization and Computational Mathematics, Tr. ISA RAN, 2006, vol. 26, pp. 48–66.

    Google Scholar 

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Correspondence to A. T. Bekishev.

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Original Russian Text © A.T. Bekishev, Yu.B. Korobochkin, 2016, published in Avtomatika i Telemekhanika, 2016, No. 7, pp. 68–85.

This paper was recommended for publication by A.I. Kibzun, a member of the Editorial Board

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Bekishev, A.T., Korobochkin, Y.B. Numerical method of estimating the maximal likelihood of a smooth parametric manifold. Autom Remote Control 77, 1180–1194 (2016). https://doi.org/10.1134/S0005117916070055

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  • DOI: https://doi.org/10.1134/S0005117916070055

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