Main Article Content

Abstract

The combination of generalization Type-I hybrid censoring and generalization Type-II hybrid censoring schemes, scheme creates a new censoring called a Unified hybrid censoring scheme. Therefore, in this study, the E-Bayesian estimation of parameters of the inverse Weibull (IW) distribution is obtained under the unified hybrid censoring scheme, and the efficiency of the proposed method was compared with the Bayesian estimator using Monte Carlo simulation and a real data set.

Keywords

E-Bayesian estimation Unified hybrid censoring scheme Inverse Weibull distribution

Article Details

How to Cite
Yaghoobzadeh Shahrastani, S., & Makhdoom, I. (2021). Estimating E-Bayesian of Parameters of Inverse Weibull Distribution Using an Unified Hybrid Censoring Scheme. Pakistan Journal of Statistics and Operation Research, 17(1), 113-122. https://doi.org/10.18187/pjsor.v17i1.2704

References

  1. Berger, J. O. (1985), Statistical Decision Theory and Bayesian Analysis, second ed., Springer-Verlag, New York. DOI: https://doi.org/10.1007/978-1-4757-4286-2
  2. Calabria, R. and G. Pulcini. (1994), Bayes 2-sample prediction for the inverse Weibull distribution, Communications in Statistics-Theory and Methods, 23 (6),1811–1824. DOI: https://doi.org/10.1080/03610929408831356
  3. Childs, A., Chandrasekhar, B., Balakrishnan, N. and Kundu, D. (2003), Exact Liklihood Inference Based on Type-I and Type-II Hybrid Censored Sampales from the Exonential distribution, Annals of the Institute of Statistical Mathematics, 55, 319-330. DOI: https://doi.org/10.1007/BF02530502
  4. Chandrasekhar, B., Childs, A. and Balakrishnan, N. (2004), Exact Liklihood Inference for the Exonential distribution under Generalized Type-I and Type-II Hybrid Censoring, Naval Research Logistics, 51, 994-1004. DOI: https://doi.org/10.1002/nav.20038
  5. Epstein, B. (1954), Truncated Life-Tests in the Exponential Case, Annals of Mathematical Statistics, 25, 555-564. DOI: https://doi.org/10.1214/aoms/1177728723
  6. Erto, P. and Rapone, M. (1984), Non-informative and practical Bayesian confidence bounds for reliable life in the Weibull model, Reliability Engineering, 7, 181-191. DOI: https://doi.org/10.1016/0143-8174(84)90016-7
  7. Han, M. (1997), The structure of hierarchical prior distribution and its applications, Chinese Operations Research and Management Science, 63, 31–40.
  8. Han, M. (2009), E-Bayesian estimation and hierarchical Bayesian estimation of failure rate, Applied Mathematical Modelling, 33(4), 1915-1922. DOI: https://doi.org/10.1016/j.apm.2008.03.019
  9. Han, M. (2011), E-Bayesian estimation of the reliability derived from Binomial distribution, Applied Mathematical Modelling, 35, 2419-2424. DOI: https://doi.org/10.1016/j.apm.2010.11.051
  10. Han, M. (2017), The E-Bayesian and hierarchical Bayesian estimations for the system reliability parameter, Communications in Statistics-Theory and Methods, 46(4), 1606-1620. DOI: https://doi.org/10.1080/03610926.2015.1024861
  11. Jaheen, Z. F. and Okasha, H. M. (2011), E-Bayesian estimation for the Burr type XII model based on type-2 censoring, Applied Mathematical Modelling, 35, 4730-4737. DOI: https://doi.org/10.1016/j.apm.2011.03.055
  12. Khan, M. S., Pasha, G. R. and Pasha, A. H. (2008), Theoretical analysis of inverse Weibull distribution, WSEAS Transactions on Mathematics, 7(2), 30–38.
  13. Lindley, D. V. and Smith, A. F. (1972), Bayes estimation for the linear model, Journal of the Royal Statistical Society-Series B, 34, 1–41. DOI: https://doi.org/10.1111/j.2517-6161.1972.tb00885.x
  14. Murthy, D.N.P. Xie, M. and Jiang, R. (2004), Weibull Models, Wiley, New York.
  15. Nelson, W. (1982), Applied Lifetime Data Analysis, Wiley, New York. DOI: https://doi.org/10.1002/0471725234
  16. Shafiei, S., Darijani, S. and Saboori, H. (2016), InverseWeibull power series distributions: properties and applications, Journal of Statistical Computation and Simulation, 86 (6), 1069–1094. DOI: https://doi.org/10.1080/00949655.2015.1049949
  17. Von Alven, W.H. (1964), Reliability engineering by ARINC, Prentice-Hall, Englewood Cliffs.
  18. Wang, J., Li, D. and Chen, D. (2012), E-Bayesian Estimation and Hierarchical Bayesian Estimation of the System Reliability Parameter, Systems Engineering Procedia, 3, 282-289. DOI: https://doi.org/10.1016/j.sepro.2011.11.031
  19. Yousefzadeh, F. (2017), E-Bayesian and hierarchical Bayesian estimations for the system reliability parameter based on asymmetric loss function, Communications in Statistics-Theory and Methods, 46(1), 1-8. DOI: https://doi.org/10.1080/03610926.2014.968736
  20. Yaghoobzadeh, S. S. (2018), Estimating E-bayesian and hierarchical bayesian of scalar parameter of Gompertz distribution under type II censoring schemes based on fuzzy data, Communications in Statistics - Theory and Methods,doi. org/10.1080/036109262017.1417438.