000			02894cam a2200325 a 4500
003			EG-GiCUC
005			20250223032141.0
008			181231s2018 ua f m 000 0 eng d
040			_aEG-GiCUC _beng _cEG-GiCUC
041	0		_aeng
049			_aDeposite
097			_aM.Sc
099			_aCai01.18.04.M.Sc.2018.Na.U
100	0		_aNada Mohamed Nabil Mohamed Elmaamon Mohamed Denana
245	1	4	_aThe use of least square method of estimating variance components in linear models / _cNada Mohamed Nabil Mohamed Elmaamon Mohamed Denana ; Supervised Elhoussainy Abdelbar Rady
246	1	5	_aاستحدام طريقة المربعات الصغري في تقدير مكونات التباين في النماذج الخطية
260			_aCairo : _bNada Mohamed Nabil Mohamed Elmaamon Mohamed Denana , _c2018
300			_a75 Leaves ; _c30cm
502			_aThesis (M.Sc.) - Cairo University - Institute of Statistical Studies and Research - Department of Statistics and Econometrics
520			_aThere exist many different methods for variance component estimation. The methods differ in the estimation principle employed, as well as in the distributional assumptions that need to be made. Most methods have been devised for the linear model, for which one assumes that the covariance matrix of the observables can be written as an unknown linear combination of known cofactor matrices. The coefficients of this linear combination are then the unknown (co)variance components that need to be estimated. In the first part of this dissertation, some of methods for variance component estimation will be presented like the minimum norm quadratic unbiased estimator (MINQUE), Henderson, the best invariant quadratic unbiased estimator (BIQUE), the maximum likelihood, ANOVA method, and the Minimum variance quadratic unbiased estimator (MIVQUE). In the second part of this dissertation, the method of weighted least-squares variance component estimation will be studied, and an elaboration on theoretical and practical aspects of the method will be given. The WLS-VCE will be shown to be a simple, flexible, and attractive VCE-method. The method is studied for two classes of weight matrices: a general weight matrix and a weight matrix from the unit weight matrix class. Finally, a simulation study will be conducted to make a comparison study between weighted least square method and maximum likelihood method, MINQUE method, BIQUE method, MIVQUE method and least square method to estimate variance components in linear model under different sample size
530			_aIssued also as CD
653		4	_aEstimating variance components
653		4	_aLeast square method
653		4	_aLinear models
700	0		_aElhoussainy Abdelbar Rady , _eSupervisor
856			_uhttp://172.23.153.220/th.pdf
905			_aNazla _eRevisor
905			_aShimaa _eCataloger
942			_2ddc _cTH
999			_c69348 _d69348