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dc.contributor.authorSiddiqui, M. M.en_US
dc.contributor.authorÇağlar, M.en_US
dc.date.accessioned2019-02-04T10:33:45Z
dc.date.available2019-02-04T10:33:45Z
dc.date.issued1994en_US
dc.identifier.issn0026-2714
dc.identifier.urihttp://hdl.handle.net/11693/48788
dc.description.abstractLet T be a continuous positive random variable representing the lifetime of an entity. This entity could be a human being, an animal or a plant, or a component of a mechanical or electrical system. For nonliving objects the lifetime is defined as the total amount of time for which the entity carries out its function satisfactorily. The concept of aging involves the adverse effects of age such as increased probability of failure due to wear. In this paper, we consider certain characteristics of the residual lifetime distribution at age t, such as the mean, median, and variance, as describing aging. Gamma and Weibull families of distributions are studied from this point of view. Explicit asymptotic expressions for the mean, variance and the percentiles of corresponding residual lifetime distributions are found. Finally these families of distributions are fitted to four sets of actual data, two of which are entirely new. The results can be used in discriminating different shape parameters.en_US
dc.language.isoEnglishen_US
dc.source.titleMicroelectronics Reliabilityen_US
dc.relation.isversionofhttps://doi.org/10.1016/0026-2714(94)90104-Xen_US
dc.titleResidual lifetime distribution and its applicationsen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineeringen_US
dc.citation.spage211en_US
dc.citation.epage227en_US
dc.citation.volumeNumber34en_US
dc.citation.issueNumber2en_US
dc.identifier.doi10.1016/0026-2714(94)90104-Xen_US
dc.publisherPergamon Pressen_US
dc.identifier.eissn1872-941X


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