On progressively first failure censored Lindley distribution
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- 作者：Madhulika Dube ; Renu Garg ; Hare Krishna
- 关键词：Lindley distribution ; Progressive first failure censoring ; Maximum likelihood estimation ; Bootstrap confidence intervals ; Bayes estimation
- 刊名：Computational Statistics
- 出版年：2016
- 出版时间：March 2016
- 年：2016
- 卷：31
- 期：1
- 页码：139-163
- 全文大小：508 KB
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Renu Garg (1)
Hare Krishna (2)
1. Department of Statistics, Maharshi Dayanand University, Rohtak, 124001, India
2. Department of Statistics, Chaudhary Charan Singh University, Meerut, 250004, India - 刊物类别：Mathematics and Statistics
- 刊物主题：Mathematics
Statistics
Statistics
Probability and Statistics in Computer Science
Probability Theory and Stochastic Processes
Economic Theory - 出版者：Physica Verlag, An Imprint of Springer-Verlag GmbH
- ISSN：1613-9658
文摘
This article deals with the progressively first failure censored Lindley distribution. Maximum likelihood and Bayes estimators of the parameter and reliability characteristics of Lindley distribution based on progressively first failure censored samples are derived. Asymptotic confidence intervals based on observed Fisher information and bootstrap confidence intervals of the parameter are constructed. Bayes estimators using non-informative and gamma informative priors are derived using importance sampling procedure and Metropolis–Hastings (MH) algorithm under squared error loss function. Also, HPD credible intervals based on importance sampling procedure and MH algorithm for the parameter are constructed. To study the performance of various estimators discussed in this article, a Monte Carlo simulation study is conducted. Finally, a real data set is studied for illustration purposes.