Algorithms for return probabilities for stochastic fluid flows

dc.contributor.authorBean, N.
dc.contributor.authorO'Reilly, M.
dc.contributor.authorTaylor, P.
dc.date.issued2005
dc.description.abstractWe consider several known algorithms and introduce some new algorithms that can be used to calculate the probability of return to the initial level in the Markov stochastic fluid flow model. We give the physical interpretations of these algorithim within the fluid flow environment. The rates of convergence are explained in terms of the physical properties of the fluid flow processes. We compare these algorithms with respect to the numbers of iterations required and their complexity. The performance of the algorithms depends on the nature of the process considered in the analysis. We illustrate this with examples and give appropriate recommendations.
dc.description.statementofresponsibilityNigel G Bean, Malgorzata M O'Reilly and Peter G Taylor
dc.identifier.citationStochastic Models, 2005; 21(1):149-184
dc.identifier.doi10.1081/STM-200046511
dc.identifier.issn1532-6349
dc.identifier.issn1532-4214
dc.identifier.orcidBean, N. [0000-0002-5351-3104]
dc.identifier.urihttp://hdl.handle.net/2440/17851
dc.language.isoen
dc.publisherTaylor & Francis Inc.
dc.relation.granthttp://purl.org/au-research/grants/arc/DP0209921
dc.source.urihttps://doi.org/10.1081/stm-200046511
dc.subjectAsmussen's iteration
dc.subjectFixed-point iterations
dc.subjectLatouche-Ramaswami method
dc.subjectMarkovian fluid model
dc.subjectNewton's method
dc.subjectReturn probabilities
dc.titleAlgorithms for return probabilities for stochastic fluid flows
dc.typeJournal article
pubs.publication-statusPublished

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