Biased Estimators for the Parameters of Linear Regression Model by Abdalrasoo.
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| Preise | 2013 | 2014 | 2015 |
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Biased Estimators for the parameters of Linear Regression model
DE PB NWISBN: 9783659388736 bzw. 3659388734, in Deutsch, LAP LAMBERT Academic Publishing, Taschenbuch, neu.
Von Händler/Antiquariat, BuySomeBooks [52360437], Las Vegas, NV, U.S.A.
Paperback. 96 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.
Paperback. 96 pages. Dimensions: 8.7in. x 5.9in. x 0.2in.This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. This item ships from multiple locations. Your book may arrive from Roseburg,OR, La Vergne,TN.
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Symbolbild
Biased Estimators for the parameters of Linear Regression model (2013)
DE PB NW RPISBN: 9783659388736 bzw. 3659388734, in Deutsch, Lap Lambert Academic Publishing Mai 2013, Taschenbuch, neu, Nachdruck.
Von Händler/Antiquariat, AHA-BUCH GmbH [51283250], Einbeck, Germany.
This item is printed on demand - Print on Demand Titel. - This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. 96 pp. Englisch.
This item is printed on demand - Print on Demand Titel. - This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. 96 pp. Englisch.
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Biased Estimators for the parameters of Linear Regression model (2013)
EN PB USISBN: 9783659388736 bzw. 3659388734, in Englisch, 96 Seiten, LAP LAMBERT Academic Publishing, Taschenbuch, gebraucht.
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Von Händler/Antiquariat, tabletopart.
This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. Paperback, Label: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, Produktgruppe: Book, Publiziert: 2013-05-08, Freigegeben: 2013-05-08, Studio: LAP LAMBERT Academic Publishing.
Von Händler/Antiquariat, tabletopart.
This work deal with biased estimation methods for estimating the parameters of general linear regression model when the data are ill-conditioned. We focus our attention on ordinary and generalized ridge regression estimators, Jackknife ridge estimators and principal components estimators. In chapter one introduction and historical review In chapter two basic concepts, definitions on linear regression model are presented. Moreover, the statistical properties of the ordinary least squares estimators are presented. Classes of biased estimators are discussed in chapter three when the data suffer from the multicollinearity problem. The procedures discussed in the preceding chapters were applied in chapter four to perform the regression analysis employing the data obtained from Midland Refineries Company in Iraq, for 12 years period in order to determine the effect of six different factors on the productivity of labor. The statistical programs, SPSS, and Minitab were employed to perform the required calculations. Paperback, Label: LAP LAMBERT Academic Publishing, LAP LAMBERT Academic Publishing, Produktgruppe: Book, Publiziert: 2013-05-08, Freigegeben: 2013-05-08, Studio: LAP LAMBERT Academic Publishing.
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Biased Estimators for the Parameters of Linear Regression Model (2013)
EN NWISBN: 9783659388736 bzw. 3659388734, in Englisch, 96 Seiten, LAP Lambert Academic Publishing, neu.
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