A regression mean estimator based on weights from auxiliary variables using mathematical programming / Heba Tallah Ahmed Eldeeb ; Supervised Ramadan Hamed , Ali Elhefnawy

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Heba Tallah Ahmed Eldeeb

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TextLanguage: English Publication details: Cairo : Heba Tallah Ahmed Eldeeb , 2012Description: 59 P. ; 25cmOther title:

استخدام البرمجة الرياضية في تقدير متوسط الانحدار المرجح بالمتغيرات المساعدة [Added title page title]

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

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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	Cai01.03.01.M.Sc.2012.He.R (Browse shelf(Opens below))		Not for loan	01010110058486000
CD - Rom	مخـــزن الرســائل الجـــامعية - البدروم	المكتبة المركزبة الجديدة - جامعة القاهرة	Cai01.03.01.M.Sc.2012.He.R (Browse shelf(Opens below))	58486.CD	Not for loan	01020110058486000

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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

Issued also as CD

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