01769cam a2200241 a 4500003000900000005001700009008004100026040002800067041000800095100003600103245012500139246006200264260005500326300003500381502012800416520081300544530002201357653004201379653002001421653001501441700003801456856003301494EG-GiCUC20250223031730.0170607s2016    ua d   f m    000 0 eng d  aEG-GiCUCbengcEG-GiCUC0 aeng0 aAhmed Elshahhat Ebrahim Elsayed10aOn a generalized progressive hybrid censoring scheme / cAhmed Elshahhat Ebrahim Elsayed ; Supervised Samir Kamel Ashour15aعن خطة مراقبة مهجنة معجلة معممة  aCairo : bAhmed Elshahhat Ebrahim Elsayed , c2016  a135 Leaves : bcharts ; c30cm  aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics    aBayesian and non-Bayesian estimators are obtained for the unknown parameters of  Weibull distribution based on the generalized Type-II progressive hybrid censoring  scheme and different special cases are obtained. The asymptotic variance covariance  matrix and approximate confidence intervals based on the asymptotic normality of the  maximum likelihood estimators are obtained. Bayes estimates and Bayes risks have been  developed under a squared error loss function using informative and non-informative  priors for the unknown Weibull parameters. It is observed that the estimators obtained are  not available in closed forms, although they can be easily evaluated for a given sample by  using suitable numerical methods. Therefore, a numerical example is considered to illustrate the proposed estimators  aIssued also as CD 4aAsymptotic variance covariance matrix 4aBayes estimator 4aBayes risk0 aSamir Kamel Ashour , eSupervisor  uhttp://172.23.153.220/th.pdf