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Computational algorithms for moments of accumulated markov and semi-markov rewards
Stockholm University, Sweden.
University of Rome La Sapienza, Rome, Italy .
Mälardalen University, School of Education, Culture and Communication, Educational Sciences and Mathematics.
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 7, p. 1453-1469Article in journal (Refereed) Published
Abstract [en]

Power moments for accumulated rewards defined on Markov and semi-Markov chains are studied. A model with mixed time-space termination of reward accumulation is considered for inhomogeneous in time rewards and Markov chains. Characterization of power moments as minimal solutions of recurrence system of linear equations, sufficient conditions for finiteness of these moments and upper bounds for them, expressed in terms of so-called test functions, are given. Backward recurrence algorithms for funding of power moments of accumulated rewards and various time-space truncation approximations reducing dimension of the corresponding recurrence relations are described.

Place, publisher, year, edition, pages
2014. Vol. 43, no 7, p. 1453-1469
Keywords [en]
Accumulated reward, High-order moment, Markov chain, Recurrence backward algorithm, Semi-Markov chain, Time-space truncation approximation
National Category
Natural Sciences
Identifiers
URN: urn:nbn:se:mdh:diva-24867DOI: 10.1080/03610926.2013.800882ISI: 000334073600011Scopus ID: 2-s2.0-84897034243OAI: oai:DiVA.org:mdh-24867DiVA, id: diva2:712728
Available from: 2014-04-16 Created: 2014-04-16 Last updated: 2017-12-05Bibliographically approved

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