000			01974cam a2200325 a 4500
003			EG-GiCUC
005			20250223031730.0
008			170607s2016 ua d f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.18.03.M.Sc.2016.Ah.O
100	0		_aAhmed Elshahhat Ebrahim Elsayed
245	1	0	_aOn a generalized progressive hybrid censoring scheme / _cAhmed Elshahhat Ebrahim Elsayed ; Supervised Samir Kamel Ashour
246	1	5	_aعن خطة مراقبة مهجنة معجلة معممة
260			_aCairo : _bAhmed Elshahhat Ebrahim Elsayed , _c2016
300			_a135 Leaves : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics
520			_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
530			_aIssued also as CD
653		4	_aAsymptotic variance covariance matrix
653		4	_aBayes estimator
653		4	_aBayes risk
700	0		_aSamir Kamel Ashour , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aEnas _eCataloger
905			_aNazla _eRevisor
942			_2ddc _cTH
999			_c61125 _d61125