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Statistical Quality Technologies pp 331–346Cite as

An Introduction of Generalized Linear Model Approach to Accelerated Life Test Planning with Type-I Censoring

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Abstract

Accelerated life tests are often expensive and difficult to conduct. Failure time censoring is anticipated because some test units do not fail over the testing period even under the accelerated stress condition. Therefore, a test plan must be carefully designed to maximize its statistical efficiency. This chapter presents an approach to optimal test planning based on the proportional hazard model of accelerated life test data. It is shown that this approach can accommodate multiple stress factors and is applicable to any failure time distribution.

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Author information

Authors and Affiliations

  1. School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Tempe, AZ, USA

    Rong Pan

  2. University of Missouri, Columbia, MO, USA

    Kangwon Seo

Authors
  1. Rong Pan
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  2. Kangwon Seo
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Corresponding author

Correspondence to Rong Pan .

Editor information

Editors and Affiliations

  1. Department of Mathematical Sciences, University of South Dakota, Vermillion, SD, USA

    Yuhlong Lio

  2. Department of Statistical Science, Southern Methodist University, Dallas, TX, USA

    Hon Keung Tony Ng

  3. Department of Statistics, Tamkang University, New Taipei, Taiwan

    Tzong-Ru Tsai

  4. Department of Statistics, University of Pretoria, Pretoria, South Africa

    Ding-Geng Chen

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Pan, R., Seo, K. (2019). An Introduction of Generalized Linear Model Approach to Accelerated Life Test Planning with Type-I Censoring. In: Lio, Y., Ng, H., Tsai, TR., Chen, DG. (eds) Statistical Quality Technologies. ICSA Book Series in Statistics. Springer, Cham. https://doi.org/10.1007/978-3-030-20709-0_14

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