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Modeling the Evolution of the Sample Distributions of Random Variables Using the Liouville Equation

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Abstract

We consider the difference approximation of the one-dimensional Liouville equation for modeling the evolution of the sample distribution density (of the nonstationary time series) estimated by a histogram. It is shown that the change in the sample density of the distribution over a certain period of time can be numerically described as a solution of the Liouville equation if the initial density distribution is strictly positive in the internal class intervals. The algorithm for determining the corresponding rate is constructed and its mechanical and statistical meaning is shown as a semigroup equivalent in the Chernoff sense to the average semigroup, which generates the evolution of the distribution function.

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Correspondence to Yu. N. Orlov.

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Translated by L. Kartvelishvili

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Kislitsin, A.A., Orlov, Y.N. Modeling the Evolution of the Sample Distributions of Random Variables Using the Liouville Equation. Math Models Comput Simul 12, 747–756 (2020). https://doi.org/10.1134/S2070048220050087

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  • DOI: https://doi.org/10.1134/S2070048220050087

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