Geodesic
Bayesian and non-Bayesian estimation of four-parameter of bivariate discrete inverse Weibull distribution with applications to model failure times, football and biological data
Filomat, Tome 34 (2020) no. 8, p. 2511

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In this paper we have considered one model, namely the bivariate discrete inverse Weibull distribution, which has not been considered in the statistical literature yet. The proposed model is a discrete analogue of Marshall-Olkin inverse Weibull distribution. Some of its important statistical properties are studied. Maximum likelihood and Bayesian methods are used to estimate the model parameters. A detailed simulation study is carried out to examine the bias and mean square error of maximum likelihood and Bayesian estimators. Finally, three real data sets are analyzed to illustrate the importance of the proposed model.
DOI : 10.2298/FIL2008511E
Classification : 60E05, 62E10, 62N05
Keywords: Bivariate discrete distributions, Joint hazard rate function, Bayesian estimation, Likelihood ratio test statistic, Simulation 
M S Eliwa; M El-Morshedy. Bayesian and non-Bayesian estimation of four-parameter of bivariate discrete inverse Weibull distribution with applications to model failure times, football and biological data. Filomat, Tome 34 (2020) no. 8, p. 2511 . doi: 10.2298/FIL2008511E
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     author = {M S Eliwa and M El-Morshedy},
     title = {Bayesian and {non-Bayesian} estimation of four-parameter of bivariate discrete inverse {Weibull} distribution with applications to model failure times, football and biological data},
     journal = {Filomat},
     pages = {2511 },
     year = {2020},
     volume = {34},
     number = {8},
     doi = {10.2298/FIL2008511E},
     language = {en},
     url = {http://geodesic.mathdoc.fr/articles/10.2298/FIL2008511E/}
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