Classical and Bayesian estimation in log-logistic distribution under random censoring

被引:15
作者
Kumar K. [1 ]
机构
[1] Department of Statistics, Central University of Haryana, Mahendergarh
关键词
Asymptotic confidence intervals; Bayes estimation; HPD credible intervals; Log-logistic distribution; Maximum likelihood estimation; MCMC method; Random censoring;
D O I
10.1007/s13198-017-0688-3
中图分类号
学科分类号
摘要
This article deals with the classical and Bayesian estimation of the parameters of log-logistic distribution using random censorship model. The maximum likelihood estimators and the asymptotic confidence intervals based on observed Fisher information matrix of the parameters are derived. Bayes estimators of the parameters under generalized entropy loss function using independent gamma priors are obtained. For Bayesian computation, Tierney–Kadane’s approximation and Markov chain Monte Carlo (MCMC) methods are used. Also, the highest posterior credible intervals of the parameters based on MCMC method are constructed. A Monte Carlo simulation study is carried out to compare the behavior of various estimators developed in this article. Finally, a real data analysis is performed for illustration purposes. © 2017, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden.
引用
收藏
页码:440 / 451
页数:11
相关论文
共 34 条
[1]  
Abbas K., Tang Y., Objective Bayesian analysis for log-logistic distribution, Commun Stat Simul Comput, 45, 8, pp. 2782-2791, (2016)
[2]  
Akaike H., A new look at the statistical models identification, IEEE Trans Autom Control, 19, 6, pp. 716-723, (1974)
[3]  
Al-Shomrani A.A., Shawky A.I., Arif O.H., Aslam M., Log-logistic distribution for survival data analysis using MCMC, SpringerPlus, 5, 1774, pp. 1-16, (2016)
[4]  
Ameraouia A., Boukhetala K., Dupuy J.-F., Bayesian estimation of the tail index of a heavy tailed distribution under random censoring, Comput Stat Data Anal, 104, pp. 148-168, (2016)
[5]  
Arnold B.C., Press S.J., Bayesian inference for Pareto populations, J Econom, 21, pp. 287-306, (1983)
[6]  
Breslow N., Crowley J., A large sample study of the life table and product limit estimates under random censorship, Ann Stat, 2, 3, pp. 437-453, (1974)
[7]  
Calibra R., Pulcini G., Point estimation under asymmetric loss functions for life truncated exponential samples, Commun Stat Theory Methods, 25, 3, pp. 585-600, (1996)
[8]  
Chen Z., Estimating the shape parameter of the log-logistic distribution, Int J Reliab Qual Saf Eng, 13, 3, pp. 257-266, (2006)
[9]  
Chen M.H., Shao Q.M., Monte Carlo estimation of Bayesian credible and HPD intervals, J Comput Graph Stat, 8, 1, pp. 69-92, (1999)
[10]  
Danish M.Y., Aslam M., Bayesian estimation for randomly censored generalized exponential distribution under asymmetric loss functions, J Appl Stat, 40, 5, pp. 1106-1119, (2013)