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Article: Analysis of data from a series of events by a geometric process model

TitleAnalysis of data from a series of events by a geometric process model
Authors
Lam, YZhu, LXChan, JSKLiu, Q
KeywordsGeometric process
Hazard function
Limiting distribution
Nonhomogeneous poisson process
Renewal process
Issue Date2004
PublisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/10255/
Citation
Acta Mathematicae Applicatae Sinica, 2004, v. 20 n. 2, p. 263-282 How to Cite?
DOI: http://dx.doi.org/10.1007/s10255-004-0167-x
AbstractGeometric process was first introduced by Lam[10,11]. A stochastic process {X i , i = 1, 2, · · ·} is called a geometric process (GP) if, for some a > 0, {a i -1X i , i = 1, 2, · · ·} forms a renewal process. In this paper, the GP is used to analyze the data from a series of events. A nonparametric method is introduced for the estimation of the three parameters in the GP. The limiting distributions of the three estimators are studied. Through the analysis of some real data sets, the GP model is compared with other three homogeneous and nonhomogeneous Poisson models. It seems that on average the GP model is the best model among these four models in analyzing the data from a series of events.
Persistent Identifierhttp://hdl.handle.net/10722/209756
ISSN
0168-9673
2022 Impact Factor: 0.8
2020 SCImago Journal Rankings: 0.309

 

DC FieldValueLanguage
dc.contributor.authorLam, Y-
dc.contributor.authorZhu, LX-
dc.contributor.authorChan, JSK-
dc.contributor.authorLiu, Q-
dc.date.accessioned2015-05-15T07:22:04Z-
dc.date.available2015-05-15T07:22:04Z-
dc.date.issued2004-
dc.identifier.citationActa Mathematicae Applicatae Sinica, 2004, v. 20 n. 2, p. 263-282-
dc.identifier.issn0168-9673-
dc.identifier.urihttp://hdl.handle.net/10722/209756-
dc.description.abstractGeometric process was first introduced by Lam[10,11]. A stochastic process {X i , i = 1, 2, · · ·} is called a geometric process (GP) if, for some a > 0, {a i -1X i , i = 1, 2, · · ·} forms a renewal process. In this paper, the GP is used to analyze the data from a series of events. A nonparametric method is introduced for the estimation of the three parameters in the GP. The limiting distributions of the three estimators are studied. Through the analysis of some real data sets, the GP model is compared with other three homogeneous and nonhomogeneous Poisson models. It seems that on average the GP model is the best model among these four models in analyzing the data from a series of events.-
dc.languageeng-
dc.publisherSpringer Verlag. The Journal's web site is located at http://link.springer.de/link/service/journals/10255/-
dc.relation.ispartofActa Mathematicae Applicatae Sinica-
dc.rightsThe final publication is available at Springer via http://dx.doi.org/[insert DOI]-
dc.subjectGeometric process-
dc.subjectHazard function-
dc.subjectLimiting distribution-
dc.subjectNonhomogeneous poisson process-
dc.subjectRenewal process-
dc.titleAnalysis of data from a series of events by a geometric process model-
dc.typeArticle-
dc.identifier.emailLam, Y: lamy@hkucc.hku.hk-
dc.identifier.emailChan, JSK: jchan@hkustasc.hku.hk-
dc.identifier.doi10.1007/s10255-004-0167-x-
dc.identifier.scopuseid_2-s2.0-42349096294-
dc.identifier.hkuros96695-
dc.identifier.volume20-
dc.identifier.issue2-
dc.identifier.spage263-
dc.identifier.epage282-
dc.publisher.placeGermany-
dc.identifier.issnl0168-9673-

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