000			03002cam a2200337 a 4500
003			EG-GiCUC
005			20250223032908.0
008			220103s2021 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.2021.Em.P
100	0		_aEman Nedal Mohamed Shams Alden Abdellattif
245	1	0	_aParameters estimation for pareto-poisson distribution / _cEman Nedal Mohamed Shams Alden Abdellattif ; Supervised Amal Soliman Hassan , Elsayed A. Elsherpieny
246	1	5	_aتقدير المعالم لتوزيع باريتو- بواسون
260			_aCairo : _bEman Nedal Mohamed Shams Alden Abdellattif , _c2021
300			_a110 Leaves : _bcharts ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Faculty of Graduate Studies for Statistical Research - Department of Mathematical Statistics
520			_aIn recent few years, compound distributions arise and applied in several areas, such as public health, economics, engineering, and industrial reliability. Compounding a continuous lifetime distribution with a discrete one is a useful method for constructing flexible distributions to facilitate better modeling of lifetime data. For this purpose, De Morais (2009) introduced a new class of distributions, called Pareto power series, based on a composition of the Pareto distribution with the power-series class of discrete distributions. He also presented some general results of this class and three special cases namely ; Pareto-Poisson, Pareto-geometric and Pareto-logarithmic distributions. He showed that the Pareto distribution is a limiting special case of the Pareto power series.This thesis aims to discuss some statistical properties of the Pareto-Poisson distribution such as: quantile function, median, mode, quartiles, mean deviations, moments and moment generating function, Rényi entropy,v - entropy, mean residual life, order statistics and stress-strength reliability. Another aim is to derive the maximum likelihood, maximum product of spacings and Bayesian estimators of the unknown parameters of Pareto-Poisson distribution under complete sampling. Under the assumption of conjugate gamma priors, the Bayes estimators are developed using squared-error loss function. Using observed Fisher information matrix, two-sided approximate confidence interval estimators of the unknown parameters are constructed. Also, two numerical applications are conducted to illustrate the usefulness of proposed methods, one of them is based on simulated data and the other is based on real-life data
530			_aIssued also as CD
653		4	_aParameters estimation
653		4	_aPareto-poisson
653		4	_aPareto-poisson distribution
700	0		_aAmal Soliman Hassan , _eSupervisor
700	0		_aElsayed A. Elsherpieny , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aShimaa _eCataloger
942			_2ddc _cTH
999			_c83814 _d83814