http://www.cnr.it/ontology/cnr/individuo/prodotto/ID37035
Maximum likelihood and Bayes prediction of current system lifetime (Articolo in rivista)
- Type
- Label
- Maximum likelihood and Bayes prediction of current system lifetime (Articolo in rivista) (literal)
- Anno
- 1996-01-01T00:00:00+01:00 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Calabria R., Pulcini G. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- Scopu (literal)
- ISI Web of Science (WOS) (literal)
- Google Scholar (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto Motori, CNR, Napoli. (literal)
- Titolo
- Maximum likelihood and Bayes prediction of current system lifetime (literal)
- Abstract
- The Power Law Process is often used to analyse failure data of repairable systems undergoing development testing where the system failure intensity decreases as a result of repeated application of corrective actions. At the end of the development program, the system failure intensity is assumed to remain constant and the current system lifetime is assumed to be exponentially distributed. In this paper, prediction limits on the current system lifetime have been derived both in the maximum likelihood and Bayesian context. Exact values and a closed form approximation of percentage points of the pivotal quantity used in the classical approach are given in the case of failure truncated testing. For both failure and time truncated testing, the Bayesian approach is developed both when no prior knowledge is available and when information on the reliability growth rate can be given. A numerical example is also given. (literal)
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- Autore CNR
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