الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The model of Dual generalized order statistics (DGOS) is of great importance in the field of reliability, life-testing and applications for medical and pharmaceutical research. In addition, it is useful in estimation and prediction that are widely used in the fields of economic, astronomy and weather forecasting.
In chapter Two, we derive new recurrence relations satisfied by the single and product moments of Dual generalized order statistics from Weibull gamma distribution. Also, we present characterizations for these distributions based on several ways: recurrence relations for single and product moments, truncated moments of certain function of the variable and hazard rate.
Chapter three, contains new recurrence relations satisfied by the single and product moments using moment generating function of Dual generalized order statistics from inverse exponential-type distribution. Recurrence relations for single and product moments of reversed order statistics and lower record value are obtained as special cases. Further, using recurrence relation for single and product moments we obtain characterization of inverse exponential-type distribution is discussed.
Chapter four, is devoted to study one-sample and two-sample Bayesian prdiction intervals of Dual generalized order statistics (DGOS) based on multiply Type-II censored data from the inverse exponential form with fixed sample size. A general prior density function is used and predictive cumulative function is obtained. The special case of inverse Weibull is considered and completed with numerical results and real life data.
Chapter five, one-sample and two-sample Bayesian prediction intervals for Dual generalized order statistics (DGOS) based on inverse exponential form using multiply Type-II censored data with random sample size are deduced. A general form of prior density functions which were suggested by [Kundu and Howlader (2010)] is used. The Bayesian prediction problem based on DGOS are also studied. The models of inverse exponential-type distribution and a general form of prior density functions are introduced. Finally, inverse Weibull is presented as special case for exponential-type distribution.