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Article: Predictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach

TitlePredictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approach
Authors
KeywordsBayesian Approach
Nonhomogeneous Poisson Process
Noninformative Prior
Prediction Intervals
Reliability Growth
Issue Date2007
PublisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csda
Citation
Computational Statistics And Data Analysis, 2007, v. 51 n. 9, p. 4254-4268 How to Cite?
AbstractNonhomogeneous Poisson process (NHPP) also known as Weibull process with power law, has been widely used in modeling hardware reliability growth and detecting software failures. Although statistical inferences on the Weibull process have been studied extensively by various authors, relevant discussions on predictive analysis are scattered in the literature. It is well known that the predictive analysis is very useful for determining when to terminate the development testing process. This paper presents some results about predictive analyses for Weibull processes. Motivated by the demand on developing complex high-cost and high-reliability systems (e.g., weapon systems, aircraft generators, jet engines), we address several issues in single-sample and two-sample prediction associated closely with development testing program. Bayesian approaches based on noninformative prior are adopted to develop explicit solutions to these problems. We will apply our methodologies to two real examples from a radar system development and an electronics system development. © 2006 Elsevier B.V. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/172432
ISSN
2015 Impact Factor: 1.179
2015 SCImago Journal Rankings: 1.283
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorYu, JWen_US
dc.contributor.authorTian, GLen_US
dc.contributor.authorTang, MLen_US
dc.date.accessioned2012-10-30T06:22:30Z-
dc.date.available2012-10-30T06:22:30Z-
dc.date.issued2007en_US
dc.identifier.citationComputational Statistics And Data Analysis, 2007, v. 51 n. 9, p. 4254-4268en_US
dc.identifier.issn0167-9473en_US
dc.identifier.urihttp://hdl.handle.net/10722/172432-
dc.description.abstractNonhomogeneous Poisson process (NHPP) also known as Weibull process with power law, has been widely used in modeling hardware reliability growth and detecting software failures. Although statistical inferences on the Weibull process have been studied extensively by various authors, relevant discussions on predictive analysis are scattered in the literature. It is well known that the predictive analysis is very useful for determining when to terminate the development testing process. This paper presents some results about predictive analyses for Weibull processes. Motivated by the demand on developing complex high-cost and high-reliability systems (e.g., weapon systems, aircraft generators, jet engines), we address several issues in single-sample and two-sample prediction associated closely with development testing program. Bayesian approaches based on noninformative prior are adopted to develop explicit solutions to these problems. We will apply our methodologies to two real examples from a radar system development and an electronics system development. © 2006 Elsevier B.V. All rights reserved.en_US
dc.languageengen_US
dc.publisherElsevier BV. The Journal's web site is located at http://www.elsevier.com/locate/csdaen_US
dc.relation.ispartofComputational Statistics and Data Analysisen_US
dc.subjectBayesian Approachen_US
dc.subjectNonhomogeneous Poisson Processen_US
dc.subjectNoninformative Prioren_US
dc.subjectPrediction Intervalsen_US
dc.subjectReliability Growthen_US
dc.titlePredictive analyses for nonhomogeneous Poisson processes with power law using Bayesian approachen_US
dc.typeArticleen_US
dc.identifier.emailTian, GL: gltian@hku.hken_US
dc.identifier.authorityTian, GL=rp00789en_US
dc.description.naturelink_to_subscribed_fulltexten_US
dc.identifier.doi10.1016/j.csda.2006.05.010en_US
dc.identifier.scopuseid_2-s2.0-34147094215en_US
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-34147094215&selection=ref&src=s&origin=recordpageen_US
dc.identifier.volume51en_US
dc.identifier.issue9en_US
dc.identifier.spage4254en_US
dc.identifier.epage4268en_US
dc.identifier.isiWOS:000246606000012-
dc.publisher.placeNetherlandsen_US
dc.identifier.scopusauthoridYu, JW=16204381100en_US
dc.identifier.scopusauthoridTian, GL=25621549400en_US
dc.identifier.scopusauthoridTang, ML=7401974011en_US
dc.identifier.citeulike3885051-

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