A comparison of estimation methods for reliability function of inverse generalized Weibull distribution under new loss function

References

• Asgharzadeh A, Rezaei R. The generalized exponential distribution as a lifetime model under different loss functions. Data Sci J. 2009;8:217–225.
   Google Scholar
• Kim C, Jung J, Chung Y. Bayesian estimation for the exponentiated Weibull model under type II progressive censoring. Statist Papers. 2011;52:53–70.
   Web of Science ®Google Scholar
• Singh SK, Singh U, Kumar D. Bayesian estimation of the exponentiated gamma parameter and reliability function under asymmetric loss function. Revstat. 2011;9(3):247–260.
   Web of Science ®Google Scholar
• Singh SK, Singh U, Kumar D. Bayes estimators of the reliability function and parameter of inverted exponential distribution using informative and non-informative priors. J Stat Comput Simul. 2013;83(12):2258–2269.
   Web of Science ®Google Scholar
• Sindhu TN, Feroze N, Aslam M, et al. Bayesian inference of mixture of two Rayleigh distributions: a new look. J Math. 2016;48(2):49–64.
   Web of Science ®Google Scholar
• Sindhu TN, Hussain Z, Aslam M. Parameter and reliability estimation of inverted Maxwell mixture model. J Stat Manag Syst. 2019;22(3):459–493.
   Web of Science ®Google Scholar
• Dey S. Bayesian estimation of the parameter and reliability function of an inverse Rayleigh distribution. Malays J Math Sci. 2012;6(1):113–124.
   Google Scholar
• Sindhu TN, Aslam M. Bayesian estimation on the proportional inverse Weibull distribution under different loss functions. Adv Agr Sci Eng Res. 2013;3(2):641–655.
   Google Scholar
• Sindhu TN, Hussain Z. Mixture of two generalized inverted exponential distributions with censored sample: properties and estimation. Statist Appl. 2018;30(3):373–391.
   Google Scholar
• Seo DG, Jung S. A comparison of three empirical reliability estimates for computerized adaptive testing (CAT) using a medical licensing examination. Front Psychol. 2018;9:681–693.
   PubMed Web of Science ®Google Scholar
• Sindhu TN, Hussain Z, Aslam M. On the Bayesian analysis of censored mixture of two Topp-Leone distribution. Sri Lankan J Appl Stat. 2019;19(1):13–30.
   Google Scholar
• Rostamian S, Nematollahi N. Estimation of stress-strength reliability in the inverse Gaussian distribution under progressively type II censored data. Math Sci. 2019;13:175–191.
   Google Scholar
• Ramos PL, Louzada F, Ramos E. Posterior properties of the Nakagami-m distribution using non-informative priors and applications in reliability. IEEE Trans Reliab. 2018;67(1):105–117.
   Web of Science ®Google Scholar
• Sindhu TN, Aslam M, Hussain Z. A simulation study of parameters for the censored shifted Gompertz mixture distribution: a Bayesian approach. J Stat Manag Syst. 2016b;19(3):423–450.
   Web of Science ®Google Scholar
• Chaturvedia A, Pathakb A, Kumar N. Statistical inferences for the reliability functions in the proportional hazard rate models based on progressive type-II right censoring. J Stat Comput Simul. 2019;89(12):2187–2217.
   Web of Science ®Google Scholar
• Sindhu TN, Aslam M, Hussain Z. Bayesian estimation on the generalized Logistic distribution under left type-II censoring. Thail Stat. 2016a;14(2):181–195.
   Web of Science ®Google Scholar
• Dmitriev YuG, Koshkin GM. Nonparametric estimation of the reliability function characteristics using auxiliary information. Russ Phys J. 2019;61(12):2197–2208.
   Web of Science ®Google Scholar
• Sankaran PG, Kumar MD. Reliability properties of proportional hazards relevation transform. Metrika. 2019;82:441–456.
   Web of Science ®Google Scholar
• Zhu T. Reliability estimation for two-parameter Weibull distribution under block censoring. Reliab Eng Syst Safety. 2020;203:DOI:10.1016/j.ress.2020.107071
   PubMed Web of Science ®Google Scholar
• Roy A, Gupta N. Reliability of a coherent system equipped with two cold standby components. Metrika. 2020;83:677–697.
   Web of Science ®Google Scholar
• Gu YK, Fan CJ, Liang LQ, et al. Reliability calculation method based on the Copula function for mechanical systems with dependent failure. Ann Oper Res. 2019;1–18. https://doi.org/10.1007/s10479-019-03202-5.
   Google Scholar
• Kotb MS, Raqab MZ. Estimation of reliability for multi-component stress-strength model based on modified Weibull distribution. Statist Papers. 2020. DOI:10.1007/s00362-020-01213-0
   Web of Science ®Google Scholar
• Karimi S, Liao H, Fan N. Flexible methods for reliability estimation using aggregate failure-time data. IISE Trans. 2021;53(1):101–115.
   Web of Science ®Google Scholar
• Jain K, Singla N, Sharma SK. The generalized inverse generalized Weibull distribution and its properties. J Probab. 2014;2014:Article ID 736101, 11 pages. Available from: http://dx.doi.org/10.1155/2014/736101.
   Google Scholar
• Keller AZ, Kamath ARR, Perera UD. Reliability analysis of CNC machine tools. Reliab Eng. 1982;3:449–473.
   Google Scholar
• Mudholkar GS, Srivastava DK, Freimer M. The exponentiated Weibull family: a reanalysis of the bus-motor-failure. Technometrics. 1995;37(4):436–445.
   Web of Science ®Google Scholar
• Lemonte AJ, Cordeiro GM. An extended Lomax distribution. Statistics. 2013;47:800–816.
   Web of Science ®Google Scholar
• Ghitany ME, Atieh B, Nadarajah S. Lindley distribution and its application. Math Comput Simul. 2008;78:493–506.
   Web of Science ®Google Scholar
• Zakerzadeh H, Mahmoudi E. A new two parameter lifetime distribution: model and properties. 2012. arXiv:1204.4248.
   Google Scholar
• Barreto-Souza W, Morais A, Cordeiro GM. The Weibull-geometric distribution. J Stat Comput Simul. 2011;81(5):645–657.
   Web of Science ®Google Scholar
• Peng B, Xu Z, Wang M. The exponentiated lindley geometric distribution with applications. Entropy. 2019;21(5):510.
   PubMed Web of Science ®Google Scholar