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A new lifetime distribution based on finite mixtures / Ehab Rasheedy Ali ; Supervised Mahmoud Riad Mahmoud , Rasha Mohamed Mandouh

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ehab Rasheedy Ali , 2017Description: 63 P. : charts ; 30cmOther title:
  • توزيع حياة جديدة مبني على الخلائط المحدودة [Added title page title]
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Dissertation note: Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics Summary: Sometimes the known statistical distributions do not suit the available data; accordingly generating a new distribution is needed. The aim of this paper was to introduce two new distributions. The first one is a one-parameter distribution which is referred to as NLM(Ý) and the second one is a power transformation of the first distribution. We refer to the second distribution as NLMP(Ü,Ý). The hazard function of NLMP(Ü,Ý) can be constant, decreasing, bathtub, decreasing - increasing, and increasing. This variety of shapes of its hazard function enables NLMP(Ü, Ý) to fit different data sets. The maximum likelihood estimate of the two parameters of NLMP(Ü,Ý) were obtained and a simulation study was carried out to examine the accuracy of the maximum likelihood estimators of the NLMP(Ü,Ý) parameters as well as the coverage probability and average width of the confidence intervals for both parameters
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.03.M.Sc.2017.Eh.N (Browse shelf(Opens below)) Not for loan 01010110074153000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.03.M.Sc.2017.Eh.N (Browse shelf(Opens below)) 74153.CD Not for loan 01020110074153000

Thesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics

Sometimes the known statistical distributions do not suit the available data; accordingly generating a new distribution is needed. The aim of this paper was to introduce two new distributions. The first one is a one-parameter distribution which is referred to as NLM(Ý) and the second one is a power transformation of the first distribution. We refer to the second distribution as NLMP(Ü,Ý). The hazard function of NLMP(Ü,Ý) can be constant, decreasing, bathtub, decreasing - increasing, and increasing. This variety of shapes of its hazard function enables NLMP(Ü, Ý) to fit different data sets. The maximum likelihood estimate of the two parameters of NLMP(Ü,Ý) were obtained and a simulation study was carried out to examine the accuracy of the maximum likelihood estimators of the NLMP(Ü,Ý) parameters as well as the coverage probability and average width of the confidence intervals for both parameters

Issued also as CD

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