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This article is cited in 3 scientific papers (total in 3 papers)
A priori generalized gamma distribution in Bayesian balance models
A. A. Kudriavtsev Department of Mathematical Statistics, Faculty of Computational Mathematics and Cybernetics, M. V. Lomonosov
Moscow State University, 1-52 Leninskiye Gory, GSP-1, Moscow 119991, Russian Federation
Abstract:
The work is devoted to the study of Bayesian balance models,
involving the division of the system parameters into two classes: supporting
system functioning positive factors and interfering with the functioning
negative factors. The balance index, defined as the ratio of the negative
factor to the positive factor, is considered. The formulation of the problem,
which consists in finding the main probabilistic characteristics (density,
distribution function, and moments) of the balance index of factors having
a priori generalized gamma distribution with the parameters of
the form of one sign, is studied. The results are formulated in terms of the
gamma-exponential function. A number of new properties of the latter are given.
It is shown that the given statements are easily reformulated for large-scale
mixtures of generalized gamma distributions with parameters of the form of
different signs. The obtained results can be widely used in models, which
describe the processes and phenomena using distributions with a positive
unlimited support.
Keywords:
Bayesian approach, generalized gamma distribution, gamma-exponential function, balance models, mixed distributions.
Received: 07.06.2019
Citation:
A. A. Kudriavtsev, “A priori generalized gamma distribution in Bayesian balance models”, Inform. Primen., 13:3 (2019), 27–33
Linking options:
https://www.mathnet.ru/eng/ia606 https://www.mathnet.ru/eng/ia/v13/i3/p27
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