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Application of the Bayesian Approach to the Construction of Statistical Estimates of Parameters of Distribution Laws of Random Variables

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Measurement Techniques Aims and scope

A Bayesian approach to the construction of effective statistical estimates of parameters of distribution laws of random variables for the Poisson and Pareto laws, exponential and uniform laws is considered. An algorithm for constructing point and interval statistical estimates for the parameters of these laws has been developed. The results of comparison with the corresponding estimates obtained by the classical maximum likelihood method are presented. The proposed algorithm can be effectively applied in the development of measurement techniques, solution of measurement problems and the development of practical methods for identifying systematic measurement errors.

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Authors and Affiliations

  1. National Research Moscow State University of Civil Engineering, Moscow, Russia

    R. Z. Khayrullin

  2. Main Scientific Metrology Center, Ministry of Defense of the Russian Federation, Moscow, Russia

    A. A. Zakutin

Authors
  1. R. Z. Khayrullin
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  2. A. A. Zakutin
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Corresponding author

Correspondence to R. Z. Khayrullin.

Additional information

Translated from Izmeritel’naya Tekhnika, No. 11 pp. 14–21, November, 2020.

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Khayrullin, R.Z., Zakutin, A.A. Application of the Bayesian Approach to the Construction of Statistical Estimates of Parameters of Distribution Laws of Random Variables. Meas Tech 63, 862–869 (2021). https://doi.org/10.1007/s11018-021-01872-x

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  • DOI: https://doi.org/10.1007/s11018-021-01872-x

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