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Statistical Inference For The Gompertz Distribution Based On Progressive Type-Ii Censored Data With Binomial Removals

Author

Listed:
  • Manoj Chacko

    (University of Kerala, Trivandrum, India)

  • Rakhi Mohan

    (University of Kerala, Trivandrum, India)

Abstract

In this paper, the problem of estimation of parameters for a two-parameterGompertz distribution is considered based on a progressively type-II censored sample with binomial removals. Together with the unknown parameters, the removal probability is also estimated. The maximum likelihood estimators of the parameters and the asymptotic variance-covariance matrix of the estimates are obtained. Bayes estimators are also obtained using different loss functions such as squared error, LINEX and general entropy. A simulation study is performed for comparison between various estimators developed in this paper. A real data set is also used for illustration.

Suggested Citation

  • Manoj Chacko & Rakhi Mohan, 2018. "Statistical Inference For The Gompertz Distribution Based On Progressive Type-Ii Censored Data With Binomial Removals," Statistica, Department of Statistics, University of Bologna, vol. 78(3), pages 251-272.
  • Handle: RePEc:bot:rivsta:v:78:y:2018:i:3:p:251-272
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    Cited by:

    1. Shikhar Tyagi & Arvind Pandey & Christophe Chesneau, 2022. "Weighted Lindley Shared Regression Model for Bivariate Left Censored Data," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 84(2), pages 655-682, November.

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