الفهرس 
Contributions to some bivariate models based on censored samples
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Abstract
This thesis studied censoring of bivariate models based on copula functionin expand. Four bivariate inverted Topp-Leone distributions with differentdependence measure have been discussed. Bivariate Weibull-G Familybased on Farlie-Gumbel-Morgenstern copula function has been introduced.Its statistical properties such as marginals, product moment, moment generation,reliability, hazard rate functions, dependence measure, and conditionaldistribution have been presented. Also, median regression model ofthe bivariate-G family has been obtained. Different special cases of thisfamily have been obtained by using Pareto, inverted Topp-Leone, Rayleigh,exponential, and Weibull distributions. Different goodness of fit measuresfor bivariate model have been explained as Kolmogorov-Smirnov statistic,Anderson-Darling, and Cramer-Von Mises. Progressive Type-II censoring ofthe bivariate model has evolved from fixed to random removal by Binomialremoval. To check this new criteria, we used bivariate odd Weibull exponentialdistribution. Also, maximum likelihood and Bayesian estimation havebeen used to estimate parameters of this model based on Progressive Type-IIcensoring scheme with Binomial removal. Different methods of confidenceintervals have been discussed as asymptotic confidence intervals, bootstrap confidence intervals, and highest posterior density. In addition to the above,the adaptive progressive hybrid censored for bivariate model based on copulafunction has been introduced. Also, Binomial removal has been addedfor this new schemes of bivariate models. The parameters of bivariate oddWeibullWeibull distribution based on adaptive progressive hybrid censoringhave been estimated by maximum likelihood and Bayesian estimation.Constant accelerated life testing for bivariate model based on progressivecensored samples with Random Removal has been introduced.