Systems and Means of Informatics
2017, Volume 27, Issue 4, pp 54-63
BAYESIAN RECURRENT MODEL OF RELIABILITY GROWTH: A PRIORI DENSITIES OF POLYNOMIAL TYPE
- A. A. Kudryavtsev
- S. I. Palionnaia
Abstract
This work is devoted to the Bayesian recurrent model of reliability growth of complex modifiable information systems. It is assumed that the key parameters of the system are unknown but the researcher obtains the information about their a priori distributions. The paper contains formulas for density and mean of marginal system's reliability when indexes of "defectiveness" and "efficiency" of the tool correcting the deficiencies in the system have a priori distributions with polynomial densities. For instance, uniform and parabolic distributions are considered. Likewise, the results for the case of degenerate distribution of one of the parameters are provided. The obtained formulas are illustrated with numerical results and plots.
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[+] About this article
Title
BAYESIAN RECURRENT MODEL OF RELIABILITY GROWTH: A PRIORI DENSITIES OF POLYNOMIAL TYPE
Journal
Systems and Means of Informatics
Volume 27, Issue 4, pp 54-63
Cover Date
2017-10-30
DOI
10.14357/08696527170404
Print ISSN
0869-6527
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
modifiable information systems; reliability theory; Bayesian approach; parabolic distribution; uniform distribution; polynomial densities
Authors
A. A. Kudryavtsev  and S. I. Palionnaia
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
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