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Discriminating among competitive distributions under censored samples / Noha Usama Mohamed ; Supervised Elsayed Ahmed Elsherpieny , Hiba Zeyada Muhammed

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Noha Usama Mohamed , 2016Description: 150 Leaves ; 30cmOther title:
  • ا{uئإؤئ}{uئإ٩٧}{uئإإ٣}{uئإئ٣}{uئإئ٣}ز {uئإ٩١}{uئإئ٣}ن ا{uئإؤئ}{uئإ٩٧}وز{uئإئ٣}{uئإأأ}{uئإ٨إ}ت ا{uئإؤئ}{uئإإ٣}{uئإ٩٧}{uئإإ٧}{uئإ٨إ}{uئإؤ٣}{uئإآ٣}{uئإ٩٤} {uئإؤئ}{uئإإ٠}{uئإأأ}{uئإئ٣}{uئإإ٧}{uئإ٨إ}ت ا{uئإؤئ}{uئإإ٣}را{uئإؤ٧}{uئإ٩١}{uئإ٩٤} [Added title page title]
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Dissertation note: Thesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics Summary: In this thesis the problem of discriminating between weibull and log logistic distribution, gamma and log logistic distribution under progressive censoring type II is considered. The maximized likelihood ratio test is used to discriminate between them. Also the problem of discriminating between gamma and log logistic under complete sample is considered. The maximized likelihood ratio test and kullback-leibler divergence is used to discriminate between them. Asymptotic distribution of the logarithm of the ratio of the maximized likelihood is obtained. These asymptotic results are used to estimate probability of correct selection, and to obtain the minimum sample size needed to discriminate between the two distribution functions. Two data sets are analyzed for illustrative purpose
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Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.03.Ph.D.2016.No.D (Browse shelf(Opens below)) Not for loan 01010110071407000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.18.03.Ph.D.2016.No.D (Browse shelf(Opens below)) 71407.CD Not for loan 01020110071407000

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

In this thesis the problem of discriminating between weibull and log logistic distribution, gamma and log logistic distribution under progressive censoring type II is considered. The maximized likelihood ratio test is used to discriminate between them. Also the problem of discriminating between gamma and log logistic under complete sample is considered. The maximized likelihood ratio test and kullback-leibler divergence is used to discriminate between them. Asymptotic distribution of the logarithm of the ratio of the maximized likelihood is obtained. These asymptotic results are used to estimate probability of correct selection, and to obtain the minimum sample size needed to discriminate between the two distribution functions. Two data sets are analyzed for illustrative purpose

Issued also as CD

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