Parameter Estimation of Bivariate Models under Some Censoring Schemes
Bivariate Models under Progressive Type-II Censoring
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In this book, the Farlie-Gumbel-Morgenstern bivariate Weibull distribution (FGMBW) has been obtained. Its statistical properties (product moment, moment generation function, reliability function and hazard rate function) have been discussed. Different methods for parameter estimation of the FGMBW distribution have been discussed, these methods are maximum likelihood estimation, inference functions for margins and semi-parametric method. Two different methods for computing the confidence interval for parameters have been discussed, which are asymptotic confidence intervals and bootstrap confide...
In this book, the Farlie-Gumbel-Morgenstern bivariate Weibull distribution (FGMBW) has been obtained. Its statistical properties (product moment, moment generation function, reliability function and hazard rate function) have been discussed. Different methods for parameter estimation of the FGMBW distribution have been discussed, these methods are maximum likelihood estimation, inference functions for margins and semi-parametric method. Two different methods for computing the confidence interval for parameters have been discussed, which are asymptotic confidence intervals and bootstrap confidence intervals. Finally, parameter estimation for the FGMBW distribution under progressive Type-II censoring samples have been introduced. In addition, a two real data sets have been introduced and analyzed to examine the model. A simulation study have been conducted to compare the preferences between estimation methods and censoring schemes.
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