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Inference on proportional hazard rate model parameter under Type-I progressively hybrid censoring scheme

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  • Leila Golparvar
  • Ahmad Parsian

Abstract

In this paper, under Type-I progressive hybrid censoring sample, we obtain maximum likelihood estimator of unknown parameter when the parent distribution belongs to proportional hazard rate family. We derive the conditional probability density function of the maximum likelihood estimator using moment-generating function technique. The exact confidence interval is obtained and compared by conducting a Monte Carlo simulation study for burr Type XII distribution. Finally, we obtain the Bayes and posterior regret gamma minimax estimates of the parameter under a precautionary loss function with precautionary index k = 2 and compare their behavior via a Monte Carlo simulation study.

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  • Leila Golparvar & Ahmad Parsian, 2016. "Inference on proportional hazard rate model parameter under Type-I progressively hybrid censoring scheme," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(24), pages 7258-7274, December.
    • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:24:p:7258-7274
    DOI: 10.1080/03610926.2014.978020
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    Cited by:

    1. van Bentum, Thomas & Cramer, Erhard, 2019. "Stochastic monotonicity of MLEs of the mean for exponentially distributed lifetimes under hybrid censoring," Statistics & Probability Letters, Elsevier, vol. 148(C), pages 1-8.

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