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A Two-stage Failure Model for Bayesian Change Point Analysis
2008 (English)In: IEEE Transactions on Reliability, ISSN 0018-9529, E-ISSN 1558-1721, Vol. 57, no 2, 388-393 p.Article in journal (Refereed) Published
Abstract [en]

This paper presents a new approach for detecting certain change-points, which may disturb the evaluation of reliability models with covariates, via a two-stage failure model, and stochastic time-lagged regression functions. The proposed model is developed with the Bayesian survival analysis method, and thus the problems for censored (or truncated) data in reliability tests can be resolved. In addition, a Markov chain Monte Carlo method based on Gibbs sampling is used to dynamically simulate the Markov chain of the parameters’ posterior distribution. Finally, a numeric example is discussed to demonstrate the proposed model.

Place, publisher, year, edition, pages
2008. Vol. 57, no 2, 388-393 p.
Identifiers
URN: urn:nbn:se:ltu:diva-7949DOI: 10.1109/TR.2008.923484Local ID: 662a955d-4ecc-418d-99c1-21cf58a8dde8OAI: oai:DiVA.org:ltu-7949DiVA: diva2:980839
Note
Upprättat; 2008; 20120508 (linjan)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2017-11-24Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
  • ieee
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  • Other style
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  • de-DE
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  • en-US
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  • nn-NB
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  • Other locale
More languages
Output format
  • html
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  • asciidoc
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