A regression mean estimator based on weights from auxiliary variables using mathematical programming /
Heba Tallah Ahmed Eldeeb
A regression mean estimator based on weights from auxiliary variables using mathematical programming / استخدام البرمجة الرياضية في تقدير متوسط الانحدار المرجح بالمتغيرات المساعدة Heba Tallah Ahmed Eldeeb ; Supervised Ramadan Hamed , Ali Elhefnawy - Cairo : Heba Tallah Ahmed Eldeeb , 2012 - 59 P. ; 25cm
Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics
A procedure for constructing a vector of regression weights less affected by outliers is considered. In the presence of multicollinearity and outliers, the proposed estimator has minimum model mean squared error. Through a simulation study, the proposed weights, the ridge regression weights, regression weights, OLS weights and raking ratio weights are compared
Mean square error Outliers Regression estimator
A regression mean estimator based on weights from auxiliary variables using mathematical programming / استخدام البرمجة الرياضية في تقدير متوسط الانحدار المرجح بالمتغيرات المساعدة Heba Tallah Ahmed Eldeeb ; Supervised Ramadan Hamed , Ali Elhefnawy - Cairo : Heba Tallah Ahmed Eldeeb , 2012 - 59 P. ; 25cm
Thesis (M.Sc.) - Cairo University - Faculty of Economics and Political Science - Department of Statistics
A procedure for constructing a vector of regression weights less affected by outliers is considered. In the presence of multicollinearity and outliers, the proposed estimator has minimum model mean squared error. Through a simulation study, the proposed weights, the ridge regression weights, regression weights, OLS weights and raking ratio weights are compared
Mean square error Outliers Regression estimator