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Assessing Material Aging from Doubly Censored Data : Weibull Distribution vs. Poisson Process

Gilles Celeux 1 Christian Lavergne 1 Yann Vernaz 1
1 IS2 - Statistical Inference for Industry and Health
Inria Grenoble - Rhône-Alpes, LBBE - Laboratoire de Biométrie et Biologie Evolutive - UMR 5558
Abstract : The versatile Weibull distribution is popular for modeling aging in failure time problems. However, in some situations the only available data are right or left censored data and estimating the Weibull distribution parameters is made much more difficult. In this paper, we consider the performance of estimating a Weibull distribution in such a doubly censored context from the maximum likelihood approach and from a non informative Bayesian point of view. Moreover, we propose an alternative model for assessing aging. It consists in assuming that left censored data arise from a Poisson process. This model can appear to provide more reliable results from such poorly informative failure time data. Both approaches are compared on the basis of numerical experiments.
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https://hal.inria.fr/inria-00072799
Contributor : Rapport de Recherche Inria <>
Submitted on : Wednesday, May 24, 2006 - 10:58:23 AM
Last modification on : Monday, February 10, 2020 - 4:36:45 PM
Long-term archiving on: : Sunday, April 4, 2010 - 11:23:03 PM

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Gilles Celeux, Christian Lavergne, Yann Vernaz. Assessing Material Aging from Doubly Censored Data : Weibull Distribution vs. Poisson Process. [Research Report] RR-3857, INRIA. 2000. ⟨inria-00072799⟩

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