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dc.contributor.advisorMatis, J. H.
dc.creatorEpperson, Jon Ohman
dc.date.accessioned2020-08-21T21:47:48Z
dc.date.available2020-08-21T21:47:48Z
dc.date.issued1976
dc.identifier.urihttps://hdl.handle.net/1969.1/DISSERTATIONS-473809
dc.descriptionVita.en
dc.description.abstractThe cumulant generating functions of some multi-compartment stochastic models having time-dependent transition rates are derived. Using these, the first and second moments of the stochastic distributions are found. Under certain assumptions concerning the initial conditions the stochastic distributions are specifically identified. The models investigated are the n-compartment mixed catenary-mammillary model and the n-compartment general irreversible model. These derivations are then used to analyze some reliability systems. In particular, the catenary portion of the mixed model is used to obtain stochastic analyses of a standby redundant system. The mixed model is used for a system wherein a component is subject to competing-risks with standby components. The general model is employed to evaluate a mission reliability with a hierarchical failure structure.en
dc.format.extentxi, 115 leaves ;en
dc.format.mediumelectronicen
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.rightsThis thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use.en
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectCompartmental analysis (Biology)en
dc.subjectStochastic processesen
dc.subjectStatisticsen
dc.subject.classification1976 Dissertation E64
dc.subject.lcshStochastic processesen
dc.subject.lcshCompartmental analysis (Biology)en
dc.titleOn the distribution of some stochastic compartmental models having time-dependent transition probabilities, with applications to reliabilityen
dc.typeThesisen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameDoctor of Philosophyen
dc.type.genredissertationsen
dc.type.materialtexten
dc.format.digitalOriginreformatted digitalen
dc.publisher.digitalTexas A&M University. Libraries
dc.identifier.oclc2835074


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