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Interval censored sampling plans for the gamma lifetime model

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  • Lu, Wanbo
  • Tsai, Tzong-Ru
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Abstract

In this article, an acceptance sampling procedure for the gamma lifetime model is established under the interval censored test. Both producer and consumer risks are considered to develop the ordinary and approximate sampling plans with grouped data. Some of the proposed sampling plans are tabulated and the use of the tables is illustrated by an example. A sensitivity study is conducted to evaluate the influence of the length of the time interval on the proposed sampling plans.

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File URL: http://www.sciencedirect.com/science/article/B6VCT-4PNFV6Y-3/2/d55511c1085df49c0331e47eb100c98e
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Bibliographic Info

Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 192 (2009)
Issue (Month): 1 (January)
Pages: 116-124

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Handle: RePEc:eee:ejores:v:192:y:2009:i:1:p:116-124

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Web page: http://www.elsevier.com/locate/eor

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Keywords: Consumer risk Gamma distribution Grouped data Maximum likelihood estimator Producer risk;

References

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  1. Zhenmin Chen & Jie Mi, 2001. "An approximate confidence interval for the scale parameter of the gamma distribution based on grouped data," Statistical Papers, Springer, vol. 42(3), pages 285-299, July.
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Cited by:
  1. Carlos Pérez-González & Arturo Fernández, 2013. "Classical versus Bayesian risks in acceptance sampling: a sensitivity analysis," Computational Statistics, Springer, vol. 28(3), pages 1333-1350, June.
  2. Fernández, Arturo J. & Pérez-González, Carlos J., 2012. "Optimal acceptance sampling plans for log-location–scale lifetime models using average risks," Computational Statistics & Data Analysis, Elsevier, vol. 56(3), pages 719-731.
  3. Fernández, Arturo J., 2012. "Minimizing the area of a Pareto confidence region," European Journal of Operational Research, Elsevier, vol. 221(1), pages 205-212.
  4. Fernández, Arturo J. & Pérez-González, Carlos J. & Aslam, Muhammad & Jun, Chi-Hyuck, 2011. "Design of progressively censored group sampling plans for Weibull distributions: An optimization problem," European Journal of Operational Research, Elsevier, vol. 211(3), pages 525-532, June.

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