| 000 | 016840000a22003610004500 | ||
|---|---|---|---|
| 003 | EG-GICUC | ||
| 005 | 20250223025742.0 | ||
| 008 | 061130s2005 ua d f m 000 0 eng d | ||
| 040 |
_aEG-GICUC _beng _cEG-GICUC |
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| 041 | 0 | _aEng | |
| 049 | _aDeposite | ||
| 097 | _aM.Sc | ||
| 099 | _aCai01.03.01.M.Sc.2005.Ha.B. | ||
| 100 | 0 | _aHamdy Fayez Farahat | |
| 245 | 1 | 0 |
_aBayesian Estimation of variance components in nested models / _cHamdy Fayez Farahat ; Supervised Tarik A.Amira , Alyaa Roshdy Zahran |
| 246 | 1 | 5 | _aتقدير مكونات التباين فى النماذج المتداخلة باسلوب بايز |
| 260 |
_aCairo : _bHamdy Fayez Farahat , _c2005 |
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| 300 |
_a87p : _bcharts ; _c30cm |
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| 502 | _aThesis (M.Sc.) - Cairo University - Faculty Of Economics and Political Science - Department Of Statistics | ||
| 520 | _aThe Bayesian approach was used , in this study , to overcome the problem of possible negative estimate for the variance components of the classical approaches However , since the full Bayesian approach needs numerical integrations to obtain the marginal posterior distributions which are impossible in many situations , some of the Markov Chain Monte Carlo (MCMC) algorithms were implemented in the thesis | ||
| 530 | _aIssued also as CD | ||
| 653 | 4 | _aBayesian inference | |
| 653 | 4 | _aGibbs sampler | |
| 653 | 4 | _aInverted gamma prior | |
| 653 | 4 | _aNested mixed models | |
| 653 | 4 | _aVariance components | |
| 700 | 0 |
_aAlyaa Roshdy Zahran , _eSupervisor |
|
| 700 | 0 |
_aTarik A.Amira , _eSupervisor |
|
| 856 | _uhttp://172.23.153.220/th.pdf | ||
| 905 |
_aEsam _eRevisor |
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| 905 |
_aMaher _eCataloger |
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| 942 |
_2ddc _cTH |
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| 999 |
_c19857 _d19857 |
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