Literature DB >> 10408181

Accelerated test models for system strength based on Birnbaum-Saunders distributions.

W J Owen1, W J Padgett.   

Abstract

Recent research in cumulative damage models for strengths of systems has yielded various statistical distributions that incorporate a system size variable and follow a generalized Birnbaum-Saunders form. These models can be unified as a three-parameter Birnbaum-Saunders-type family of distributions, where the third parameter arises from the size variable through the cumulative damage approach. In this paper, the generalized three-parameter Birnbaum-Saunders distribution is characterized, and examples of cumulative damage models for system strength that fit this form are given. Also, estimation and asymptotic theory are developed for the generalized distribution, and illustrations are presented for experimental strength data for carbon composite materials.

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Year:  1999        PMID: 10408181     DOI: 10.1023/a:1009649428243

Source DB:  PubMed          Journal:  Lifetime Data Anal        ISSN: 1380-7870            Impact factor:   1.588


  4 in total

1.  Inference from accelerated degradation and failure data based on Gaussian process models.

Authors:  W J Padgett; Meredith A Tomlinson
Journal:  Lifetime Data Anal       Date:  2004-06       Impact factor: 1.588

2.  Accelerated degradation models for failure based on geometric Brownian motion and gamma processes.

Authors:  Chanseok Park; W J Padgett
Journal:  Lifetime Data Anal       Date:  2005-12       Impact factor: 1.588

3.  Accelerated test system strength models based on Birnbaum-Saunders distribution: a complete Bayesian analysis and comparison.

Authors:  S K Upadhyay; Bhaswati Mukherjee; Ashutosh Gupta
Journal:  Lifetime Data Anal       Date:  2009-03-03       Impact factor: 1.588

4.  A new class of survival regression models with heavy-tailed errors: robustness and diagnostics.

Authors:  Michelli Barros; Gilberto A Paula; Víctor Leiva
Journal:  Lifetime Data Anal       Date:  2008-03-22       Impact factor: 1.588

  4 in total

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