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Bayesian inference for seasonal ARMA models : A gibbs sampling approavh / Ayman Ahmed Amin Abdellah ; Supervised Mohamed A. Ismail , Emad E. A. Soliman

By: Contributor(s): Material type: TextTextLanguage: English Publication details: Cairo : Ayman Ahmed Amin Abdellah , 2009Description: 71 P. : charts ; 25cmOther title:
  • الموسمية ARMA الاستدلال البيزى لنماذج : معاينة جبس [Added title page title]
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  • Issued also as CD
Dissertation note: Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics Summary: The main objective of this study is to develop a bayesian inference for multiplicative seasonal ARMA models by implementing a fast, easy and accurate gibbs sampling algorithm. Bayesian analysis of seasonal ARMA model is difficult since the likelihood function is analytically intractable, which causes problems in prior specification and posterior analysis
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Item type Current library Home library Call number Copy number Status Date due Barcode
Thesis Thesis قاعة الرسائل الجامعية - الدور الاول المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.03.01.M.Sc.2009.Ay.B (Browse shelf(Opens below)) Not for loan 01010110051877000
CD - Rom CD - Rom مخـــزن الرســائل الجـــامعية - البدروم المكتبة المركزبة الجديدة - جامعة القاهرة Cai01.03.01.M.Sc.2009.Ay.B (Browse shelf(Opens below)) 51877.CD Not for loan 01020110051877000

Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics

The main objective of this study is to develop a bayesian inference for multiplicative seasonal ARMA models by implementing a fast, easy and accurate gibbs sampling algorithm. Bayesian analysis of seasonal ARMA model is difficult since the likelihood function is analytically intractable, which causes problems in prior specification and posterior analysis

Issued also as CD

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