Data-analytic and monitoring schemes for a class of discrete point processes.

Persistent Link:
http://hdl.handle.net/10150/185347
Title:
Data-analytic and monitoring schemes for a class of discrete point processes.
Author:
Chandramouli, Yegnanarayanan.
Issue Date:
1991
Publisher:
The University of Arizona.
Rights:
Copyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.
Abstract:
A point process model for the packet stream arising in teletraffic processes is the discrete, non-negative integer-valued, stationary process introduced by Neuts and Pearce. In this thesis, we examine an empirical approach to develop a monitoring scheme for that point process. Monitoring is a procedure of tracking a stochastic process to identify quickly the development of anomalous situations in the evolution of that process and detect their assignable causes. Further, a data-analytic scheme to evaluate the order of a Markov chain that quantifies the local dependence embedded in the point process and Walsh spectral techniques are examined.
Type:
text; Dissertation-Reproduction (electronic)
Keywords:
Dissertations, Academic; Operations research.
Degree Name:
Ph.D.
Degree Level:
doctoral
Degree Program:
Systems and Industrial Engineering; Graduate College
Degree Grantor:
University of Arizona
Advisor:
Neuts, Marcel F.

Full metadata record

DC FieldValue Language
dc.language.isoenen_US
dc.titleData-analytic and monitoring schemes for a class of discrete point processes.en_US
dc.creatorChandramouli, Yegnanarayanan.en_US
dc.contributor.authorChandramouli, Yegnanarayanan.en_US
dc.date.issued1991en_US
dc.publisherThe University of Arizona.en_US
dc.rightsCopyright © is held by the author. Digital access to this material is made possible by the University Libraries, University of Arizona. Further transmission, reproduction or presentation (such as public display or performance) of protected items is prohibited except with permission of the author.en_US
dc.description.abstractA point process model for the packet stream arising in teletraffic processes is the discrete, non-negative integer-valued, stationary process introduced by Neuts and Pearce. In this thesis, we examine an empirical approach to develop a monitoring scheme for that point process. Monitoring is a procedure of tracking a stochastic process to identify quickly the development of anomalous situations in the evolution of that process and detect their assignable causes. Further, a data-analytic scheme to evaluate the order of a Markov chain that quantifies the local dependence embedded in the point process and Walsh spectral techniques are examined.en_US
dc.typetexten_US
dc.typeDissertation-Reproduction (electronic)en_US
dc.subjectDissertations, Academicen_US
dc.subjectOperations research.en_US
thesis.degree.namePh.D.en_US
thesis.degree.leveldoctoralen_US
thesis.degree.disciplineSystems and Industrial Engineeringen_US
thesis.degree.disciplineGraduate Collegeen_US
thesis.degree.grantorUniversity of Arizonaen_US
dc.contributor.advisorNeuts, Marcel F.en_US
dc.contributor.committeememberYakowitz, Sidney J.en_US
dc.contributor.committeememberSanchez, Paul J.en_US
dc.contributor.committeememberMaier, Robert S.en_US
dc.identifier.proquest9121537en_US
dc.identifier.oclc708653442en_US
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