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This article is cited in 2 scientific papers (total in 2 papers)
A priori generalized Frechet distribution in Bayesian balance models
A. A. Kudryavtseva, S. I. Palionnaiaa, V. S. Shorginb a Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov
Moscow State University, 1-52 Leninskiye Gory, GSP-1, Moscow 119991,
Russian Federation
b Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119133, Russian Federation
Abstract:
This article continues a series of authors' works in the field of applying the Bayesian approach to queuing, reliability and balance models. In the framework of this approach, when complex aggregates are considered, all parameters affecting the functioning of the system are divided into two classes: contributing and preventing correct functioning of the system. The probabilistic characteristics of the balance index — the ratio of factors that negatively affect the operation of the system to positively influencing factors — are studied under the assumption that the factors are random variables with known a priori distributions. In this work, the probabilistic characteristics of the system's balance index are concerned in the case when both factors have an a priori generalized Frechet distribution. The results are presented in terms of a special gamma exponential function.
Keywords:
Bayesian approach, generalized Frechet distribution, gamma exponential function, balance models, mixed distributions.
Received: 12.03.2019
Citation:
A. A. Kudryavtsev, S. I. Palionnaia, V. S. Shorgin, “A priori generalized Frechet distribution in Bayesian balance models”, Sistemy i Sredstva Inform., 29:2 (2019), 39–45
Linking options:
https://www.mathnet.ru/eng/ssi638 https://www.mathnet.ru/eng/ssi/v29/i2/p39
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