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Reliability inference for a general lower-truncated family of distributions under records

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  • Liang Wang

Abstract

Based on record values, point and interval estimators are proposed in this paper for the parameters of a general lower-truncated family of distributions. Maximum likelihood and bias-corrected estimators are obtained for unknown model parameters. Based on a sufficient and complete statistic, the bias-corrected estimator is also shown to be uniformly minimum variance unbiased estimator. Different exact confidence intervals and exact confidence regions are constructed for the both model and truncated parameters, and other confidence interval estimates based on asymptotic distribution theory and bootstrap approaches are obtained as well. Finally, two real-life examples and a numerical study are presented to illustrate the performance of our methods.

Suggested Citation

  • Liang Wang, 2017. "Reliability inference for a general lower-truncated family of distributions under records," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 46(12), pages 6151-6173, June.
    • Handle: RePEc:taf:lstaxx:v:46:y:2017:i:12:p:6151-6173
    DOI: 10.1080/03610926.2015.1122057
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