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Nonlinearly  Perturbed Markov Chains  and  Information Networks
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, School of Physical Sciences, Makerere University, Kampala, Uganda. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Department of Mathematics, College of Natural and Applied Sciences, University of Dar es Salaam,Tanzania. (MAM)
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. Stockholm University, Sweden. (MAM)ORCID iD: 0000-0002-2626-5598
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics. (MAM)ORCID iD: 0000-0003-4554-6528
Show others and affiliations
2019 (English)In: Proceedings of 18th Applied Stochastic Models and Data Analysis International Conference with the Demographics 2019 Workshop, Florence, Italy: 11-14 June, 2019 / [ed] Christos H. Skiadas, ISAST: International Society for the Advancement of Science and Technology , 2019, p. 51-79Conference paper, Published paper (Refereed)
Abstract [en]

The paper is devoted to studies of perturbed Markov chains commonly used for description of information networks. In such models, the matrix of transition probabilities for the corresponding Markov chain is usually regularised by adding  a special damping matrix multiplied by a small damping (perturbation) parameter ε. In this paper, we present results of the detailed perturbation analysis of Markov chains with damping component and numerical experiments supporting and illustrating the results of this perturbation analysis.

Place, publisher, year, edition, pages
ISAST: International Society for the Advancement of Science and Technology , 2019. p. 51-79
Keywords [en]
Markov chain, Damping component, Information network, Regular perturbation, Singular perturbation, Stationary distribution, Asymptotic expansion, Rate of convergence, Coupling, Ergodic theorem, Triangular array mode
National Category
Probability Theory and Statistics
Research subject
Mathematics/Applied Mathematics
Identifiers
URN: urn:nbn:se:mdh:diva-47082ISBN: 978-618-5180-33-1 (electronic)OAI: oai:DiVA.org:mdh-47082DiVA, id: diva2:1394752
Conference
ASMDA2019, 18th Applied Stochastic Models and Data Analysis International Conference
Funder
Sida - Swedish International Development Cooperation AgencyAvailable from: 2020-02-20 Created: 2020-02-20 Last updated: 2020-02-24Bibliographically approved

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