 Dependence patterns for modeling simultaneous eventsRodrÃguez, Joanna, Rosa E. Lillo and RamÃrez-Cobo, Pepa Reliability Engineering and System Safety, 2016, vol. 154, issue C, 19-30 Abstract: In this paper we examine in detail some of the modeling capabilities of the stationary m-state BMAP, with simultaneous events up to size k, noted BMAPm(k). Specifically, we study the forms of the auto-correlation functions of the inter-event times and event sizes. We provide a novel characterization of the functions which is suitable for analyzing the dependence patterns. In particular, this allows one to prove a geometrically decrease to zero of the functions and to identify four correlation patterns, when m=2 . The case m≥3 is illustrated via an extensive simulation study, from which it can be deduced that, as expected, richer structures can be obtained as m increases. In addition, the influence of the dependence patterns for both auto-correlation functions for the BMAP2(2) in the counting process has been explored through an empirical analysis. Keywords: Batch Markovian arrival process (BMAP); Dependent inter-event times; Dependent event arrivals size; Autocorrelation function (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:154:y:2016:i:c:p:19-30 DOI: 10.1016/j.ress.2016.05.008 Access Statistics for this article Reliability Engineering and System Safety is currently edited by Carlos Guedes Soares More articles in Reliability Engineering and System Safety from Elsevier |
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