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Analysis of empirical estimates obtained for gibbs distribution parameters by the maximum likelihood method

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Abstract

The paper examines the properties of consistency and asymptotic normality of the maximum likelihood estimate for Markov sequences with Gibbs distribution. Theorems are formulated and proved that allow approximating the criterion function of a Markov process with a unique minimum point by its empirical estimate. The results can be used to analyze the convergence of unknown parameters to their true values.

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Authors and Affiliations

  1. V. M. Glushkov Institute of Cybernetics, National Academy of Sciences of Ukraine, Kyiv, Ukraine

    O. S. Samosonok

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  1. O. S. Samosonok
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Correspondence to O. S. Samosonok.

Additional information

Translated from Kibernetika i Sistemnyi Analiz, No. 2, March–April, 2013, pp. 178–187.

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Samosonok, O.S. Analysis of empirical estimates obtained for gibbs distribution parameters by the maximum likelihood method. Cybern Syst Anal 49, 316–324 (2013). https://doi.org/10.1007/s10559-013-9514-3

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  • DOI: https://doi.org/10.1007/s10559-013-9514-3

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