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Computational Algorithms for Moments of Accumulated Markov and Semi-Markov Rewards:  
Stockholm University, Faculty of Science, Department of Mathematics.
University of Rome "La Sapienza".
Mälardalen University.
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415X, Vol. 43, no 7, 1453-1469 p.Article in journal (Refereed) Published
Abstract [en]

Power moments for accumulated rewards defined on Markov and semi-Markov chains are studied. A model with mixed timespace 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. Applications to finding of moments for accumulated rewards for complex insurance contracts are presented as well as results of numerical experimental studies.

Place, publisher, year, edition, pages
Stockholm, Sweden, 2014. Vol. 43, no 7, 1453-1469 p.
Keyword [en]
Accumulated reward, Markov chain, Semi-Markov chain, Recurrence backward algorithm, Insurance rewards
National Category
Probability Theory and Statistics
Research subject
Mathematical Statistics
URN: urn:nbn:se:su:diva-102741DOI: 10.1080/03610926.2013.800882ISI: 000334073600011OAI: diva2:713072
Dmitrii Silvestrov


Available from: 2014-04-18 Created: 2014-04-18 Last updated: 2014-06-23Bibliographically approved

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ReferencesLink to record
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