الفهرس Only 14 pages are availabe for public view
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Abstract
In this thesis, presents point estimates of parameters for exponentiated Weibull Poisson distribution based on generalized order statistics using maximum likelihood and Bayesian methods. The asymptotic variances and covariance matrix and confidence interval estimates of parameters are derived based on generalized order statistics. Maximum likelihood and Bayesian predictive (point and interval) of the first future observations are obtained based on generalized order statistics. All results are specialized to type II censored data and upper record values. Bayesian prediction estimators of the first future observation from exponentiated Weibull Poisson distribution are obtained by using different loss functions. All estimation algorithms and numerical studies are carried out to asses these effects using MathCAD (14) statistical package