Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems

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dc.contributor.author Bretó, Carles
dc.contributor.author Ionides, Edward L.
dc.contributor.editor Universidad Carlos III de Madrid. Departamento de Estadística
dc.date.accessioned 2011-07-15T10:28:24Z
dc.date.available 2011-07-15T10:28:24Z
dc.date.issued 2011-07
dc.identifier.uri http://hdl.handle.net/10016/11694
dc.description.abstract We propose an infinitesimal dispersion index for Markov counting processes. We show that, under standard moment existence conditions, a process is infinitesimally (over-) equi-dispersed if, and only if, it is simple (compound), i.e. it increases in jumps of one (or more) unit(s), even though infinitesimally equi-dispersed processes might be under-, equi- or over-dispersed using previously studied indices. Compound processes arise, for example, when introducing continuous-time white noise to the rates of simple processes resulting in Lévy-driven SDEs. We construct multivariate infinitesimally over dispersed compartment models and queuing networks, suitable for applications where moment constraints inherent to simple processes do not hold.
dc.format.mimetype text/plain
dc.format.mimetype application/pdf
dc.language.iso eng
dc.relation.ispartofseries UC3M Working papers. Statistics and Econometrics
dc.relation.ispartofseries 11-14
dc.rights Atribución-NoComercial-SinDerivadas 3.0 España
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject.other Continuous time
dc.subject.other Counting Markov process
dc.subject.other Birth-death process
dc.subject.other Environmental stochasticity
dc.subject.other Infinitesimal over-dispersion
dc.subject.other Simultaneous events
dc.title Compound Markov counting processes and their applications to modeling infinitesimally over-dispersed systems
dc.type workingPaper
dc.subject.eciencia Estadística
dc.rights.accessRights openAccess
dc.type.version submitedVersion
dc.identifier.uxxi DT/0000000942
dc.identifier.repec ws111914
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