Informatics and Applications
2019, Volume 13, Issue 1, pp 62-66
A PRIORI FRECHET AND SCALED INVERSE CHI DISTRIBUTION IN BAYESIAN BALANCE MODELS
- A. A. Kudryavtsev
- S. I. Palionnaia
- V. S. Shorgin
Abstract
This article continues a series of authors' works in the field of modeling queuing systems using the Bayesian approach. The problem's statement is extended to a wider class of applied research - the study of the balance index of factors affecting the functioning of the system. It is assumed that the model parameters are divided into two classes, one of which includes factors that have a positive impact on the functioning of a complex aggregate and the other includes those that interferes with the functioning. The effectiveness of the system under study, of course, depends on the ratio of positive and negative factors, called the balance index. In the framework of the Bayesian approach, it is assumed that the factors are random variables with known a priori distributions. In a wide range of applied problems, it is reasonable to use gamma-type distributions. In this paper, the mixtures of particular generalized gamma distribution cases - the Frechet distribution and the scaled inverse chi distribution - are considered.
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[+] About this article
Title
A PRIORI FRECHET AND SCALED INVERSE CHI DISTRIBUTION IN BAYESIAN BALANCE MODELS
Journal
Informatics and Applications
2019, Volume 13, Issue 1, pp 62-66
Cover Date
2019-04-30
DOI
10.14357/19922264190109
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
Bayesian approach; scaled inverse chi distribution; Frechet distribution; gamma-exponential function; balance models; mixed distributions
Authors
A. A. Kudryavtsev  , S. I. Palionnaia , and V. S. Shorgin 
Author Affiliations
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
Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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