Bayesian and Non-Bayesian Estimation for the Bivariate Inverse Weibull Distribution Under Progressive Type-II Censoring
Tóm tắt
Recently, bivariate inverse Weibull distribution was derived; many of its properties have been discussed. Progressive Type-II censoring for bivariate inverse Weibull distribution has been proposed. The problem of estimating the unknown parameters of this distribution in the presence of progressive Type-II censoring by both Maximum likelihood and Bayesian estimation methods is considered in this paper. Moreover, asymptotic and bootstrap confidence intervals for the model parameters are obtained. Simulation study and a real data set are presented to illustrate the proposed procedure.
Tài liệu tham khảo
Hougaard P, Harvald B, Holm NV (1992) Measuring the similarities between the lifetimes of adult Danish twins born between 1881–1930. J Am Stat Assoc 87(417):17–24
Lin DY, Sun W, Ying Z (1999) Nonparametric estimation of the gap time distribution for serial events with censored data. Biometrika 86(1):59–70
Eliwa MS, El-Morshedy M (2019) Bivariate Gumbel-G family of distributions: statistical properties, Bayesian and Non-Bayesian estimation with application. Ann Data Sci 6(1):39–60
Almetwally EM, Muhammed HZ, El-Sherpieny ESA (2020) Bivariate Weibull distribution: properties and different methods of estimation. Ann Data Sci 7(1):163–193
Almetwally EM, Muhammed HZ (2020) On a bivariate Fréchet distribution. J Stat Appl Probab 9(1):1–21
Yousaf F, Ali S, Shah I (2019) Statistical inference for the chen distribution based on upper record values. Ann Data Sci 6(4):831–851
Sultana F, Tripathi YM, Wu SJ, Sen T (2020) Inference for Kumaraswamy distribution based on Type I progressive hybrid censoring. Ann Data Sci. https://doi.org/10.1007/s40745-020-00283-z
El-Sherpieny ESA, Almetwally EM, Muhammed HZ (2020) Progressive Type-II hybrid censored schemes based on maximum product spacing with application to Power Lomax distribution. Phys A Stat Mech Appl 553(1):124251
Almetwally EM, Almongy HM, Rastogi MK, Ibrahim M (2020) Maximum product spacing estimation of Weibull distribution under adaptive Type-II progressive censoring schemes. Ann Data Sci 7(2):257–279
Tien JM (2017) Internet of things, real-time decision making, and artificial intelligence. Ann Data Sci 4(2):149–178
Muhammed HZ (2016) Bivariate inverse Weibull distribution. J Stat Comput Simul 86(12):1–11
Marshall AW, Olkin I (1967) A multivariate exponential distribution. J Am Stat Assoc 62(317):30–44
Balakrishnan N, Kim JA (2005) Point and interval estimation for bivariate normal distribution based on progressively Type-II censored data. Commun Stat Theory Methods 34(6):1297–1347
Almetwally EM (2019) Parameter estimation of bivariate models under some censoring schemes. Master Thesis, Faculty of Graduate Studies for Statistical Research, Cairo University
El-Sherpieny ESA, Muhammed HZ, Almetwally EM (2019) Parameter estimation of the bivariate Weibull distribution under progressive Type-II censored samples. J Mod Appl Stat Methods (to appear)
Efron B (1982) The jackknife, the bootstrap and other sampling plans. In: CBMS-NSF regional conference series in applied mathematics. SIAM, Philadelphia, p 38
Tibshirani RJ, Efron B (1993) An introduction to the bootstrap. Monogr Stat Appl Probab 57:1–436
Hall P (1988) Theoretical comparison of bootstrap confidence intervals. Ann Stat 16(3):927–953
Kreiss JP, Paparoditis E (2011) Bootstrap methods for dependent data: a review. J Korean Stat Soc 40(4):357–378
Kundu D, Gupta AK (2013) Bayes estimation for the Marshal–Olkin bivariate Weibull distribution. Comput Stat Data Anal 57(1):271–281
Metropolis N, Rosenbluth AW, Rosenbluth MN, Teller AH, Teller E (1953) Equation of state calculations by fast computing machines. J Chem Phys 21(6):1087–1092
Meintanis SG (2007) Test of fit for Marshall-Olkin distributions with applications. J Stat Plan Inference 137(12):3954–3963