On Burr XII Distribution Analysis Under Progressive Type-II Hybrid Censored Data

M. Noori Asl, R. Arabi Belaghi () and H. Bevrani
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M. Noori Asl: University of Tabriz
R. Arabi Belaghi: University of Tabriz
H. Bevrani: University of Tabriz

Methodology and Computing in Applied Probability, 2017, vol. 19, issue 2, 665-683

Abstract: Abstract In the current paper, based on progressive type-II hybrid censored samples, the maximum likelihood and Bayes estimates for the two parameter Burr XII distribution are obtained. We propose the use of expectation-maximization (EM) algorithm to compute the maximum likelihood estimates (MLEs) of model parameters. Further, we derive the asymptotic variance-covariance matrix of the MLEs by applying the missing information principle and it can be utilized to construct asymptotic confidence intervals (CIs) for the parameters. The Bayes estimates of the unknown parameters are obtained under the assumption of gamma priors by using Lindley’s approximation and Markov chain Monte Carlo (MCMC) technique. Also, MCMC samples are used to construct the highest posterior density (HPD) credible intervals. Simulation study is conducted to investigate the accuracy of the estimates and compare the performance of CIs obtained. Finally, one real data set is analyzed for illustrative purposes.

Keywords: Bayesian estimate; EM algorithm; Missing information principle; Lindley’s approximation; Importance sampling; Progressive type-II hybrid censoring; 62F10; 62N01; 62N02 (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s11009-016-9514-7

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