Estimation and prediction in warranty models / Eman Aly Eldessouky Nassef ; Supervised Ahmed Fouaad Mohamed Attia , Essam Abouelkassam Ahmed

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Eman Aly Eldessouky Nassef

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Language: Eng Publication details: Cairo : Eman Aly Eldessouky Nassef , 2008Description: 107Leaves ; 30cmOther title:

التقدير و التنبؤ فى نماذج الضمان [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: This thesis deals with applying warranty models on the failure time which has log - logistic distribution.Maximum likelihood and Bayesian estimate for the unknown parameters of distribution are obtained

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Item type	Current library	Home library	Call number	Copy number	Status	Barcode
Thesis	قاعة الرسائل الجامعية - الدور الاول	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.18.03.Ph.D.2008.Em.E (Browse shelf(Opens below))		Not for loan	01010110048638000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.18.03.Ph.D.2008.Em.E (Browse shelf(Opens below))	48638.CD	Not for loan	01020110048638000

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Previous	Cai01.18.03.Ph.D.2007.Wa.P Progressive interval censoring samples with random removal /	Cai01.18.03.Ph.D.2007.Wa.P Progressive interval censoring samples with random removal /	Cai01.18.03.Ph.D.2008.Em.E Estimation and prediction in warranty models /	Cai01.18.03.Ph.D.2008.Em.E Estimation and prediction in warranty models /	Cai01.18.03.Ph.D.2008.Na.W Weibull - weibull length - biased mixture distributions in life testing models /	Cai01.18.03.Ph.D.2008.Na.W Weibull - weibull length - biased mixture distributions in life testing models /	Cai01.18.03.Ph.D.2010.Mo.I Inference for the extreme value distributions using bootstrap and censored samples /	Next

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

This thesis deals with applying warranty models on the failure time which has log - logistic distribution.Maximum likelihood and Bayesian estimate for the unknown parameters of distribution are obtained

Issued also as CD

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