E-Bayesian estimation of Burr Type XII model based on adaptive Type-Ⅱ progressive hybrid censored data

Hassan Okasha; Mazen Nassar; Saeed A. Dobbah; Hassan Okasha; Mazen Nassar; Saeed A. Dobbah

doi:10.3934/math.2021247

AIMS Mathematics

2021, Volume 6, Issue 4: 4173-4196. doi: 10.3934/math.2021247

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Research article

E-Bayesian estimation of Burr Type XII model based on adaptive Type-Ⅱ progressive hybrid censored data

1.
Department of Statistics, Faculty of Science, King AbdulAziz University, Box 80200, Jeddah 21589, Saudi Arabia
2.
Department of Mathematics, Faculty of Science, Al-Azhar University, Nasr City, 11884, Cairo, Egypt
3.
Department of Statistics, Faculty of Commerce, Zagazig University, Egypt

Received: 27 September 2020 Accepted: 03 February 2021 Published: 07 February 2021
MSC : 62F15, 62F30, 62F86

In this paper, we obtain the E-Bayesian estimation of the parameter and the reliability function of the Burr type-XII distribution under adaptive progressive Type-Ⅱ censoring scheme. The E-Bayesian estimation is investigated using three different prior distributions based on squared error and LINEX loss functions. The properties of the E-Bayesian estimation and the E-posterior risk under squared error and LINEX loss functions are also discussed. An extensive simulation study is conducted to compare the behaviour of the E-Bayesian estimation with the corresponding Bayes and maximum likelihood estimators. We analyze one real data set to show the applicability of the different estimators in practice.
- Burr type-XII,
- Bayesian estimation,
- E-Bayesian estimation,
- E-posterior risk,
- adaptive type-Ⅱ progressive hybrid censored data
Citation: Hassan Okasha, Mazen Nassar, Saeed A. Dobbah. E-Bayesian estimation of Burr Type XII model based on adaptive Type-Ⅱ progressive hybrid censored data[J]. AIMS Mathematics, 2021, 6(4): 4173-4196. doi: 10.3934/math.2021247

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Abstract

In this paper, we obtain the E-Bayesian estimation of the parameter and the reliability function of the Burr type-XII distribution under adaptive progressive Type-Ⅱ censoring scheme. The E-Bayesian estimation is investigated using three different prior distributions based on squared error and LINEX loss functions. The properties of the E-Bayesian estimation and the E-posterior risk under squared error and LINEX loss functions are also discussed. An extensive simulation study is conducted to compare the behaviour of the E-Bayesian estimation with the corresponding Bayes and maximum likelihood estimators. We analyze one real data set to show the applicability of the different estimators in practice.

References

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