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Estimating a Finite Mixed Exponential Distribution under Progressively Type-II Censored Data

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  • Yuzhu Tian
  • Maozai Tian
  • Qianqian Zhu

Abstract

The Type-II progressive censoring scheme has become very popular for analyzing lifetime data in reliability and survival analysis. However, no published papers address parameter estimation under progressive Type-II censoring for the mixed exponential distribution (MED), which is an important model for reliability and survival analysis. This is the problem that we address in this paper. It is noted that maximum likelihood estimation of unknown parameters cannot be obtained in closed form due to the complicated log-likelihood function. We solve this problem by using the EM algorithm. Finally, we obtain closed form estimates of the model. The proposed methods are illustrated by both some simulations and a case analysis.

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  • Yuzhu Tian & Maozai Tian & Qianqian Zhu, 2014. "Estimating a Finite Mixed Exponential Distribution under Progressively Type-II Censored Data," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 43(17), pages 3762-3776, September.
    • Handle: RePEc:taf:lstaxx:v:43:y:2014:i:17:p:3762-3776
    DOI: 10.1080/03610926.2012.752843
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    Cited by:

    1. Tian, Yuzhu & Zhu, Qianqian & Tian, Maozai, 2015. "Estimation for mixed exponential distributions under type-II progressively hybrid censored samples," Computational Statistics & Data Analysis, Elsevier, vol. 89(C), pages 85-96.

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