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A revision on Multicollinearity and Augmentation Methods: Multicollinearity and Augmentation Methods - Couverture souple
Synopsis
This book presents a new augmentation method to eliminate the multicollinearity in datasets that contain several correlated predictor variables. The objective in mind is to reduce the estimation error of the regression coefficients. The main contribution of this work consists in offering a new alternative to eliminate multicollinearity in datasets by using small runs which are added in a sequential manner. The algorithm proposed will indicate the point in which the augmentations have sufficiently contributed to find the true regression model. The procedure is based on addition of new observations to the point in which an appropriate regression model can be constructed. The new information is obtained through designed experiments using the R3 algorithm as a guideline to perform the augmentations and the Ridge Trace and VIF statistic as verification tools that help to determine the point in which the correlations have been significantly reduced. The final result is a linear regression model that accurately represents the process under study.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
M.I.E. Russell Pérez González received his I.E. from Instituto de Tuxtla Gutiérrez, Chiapas and his Masters from Technological Institute of Celaya, Guanajuato. M.I.E. Russell´s degrees are all in Industrial Engineering. His concentration area includes experimental design, mechanical design and technology management.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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A revision on Multicollinearity and Augmentation Methods
Edité par
LAP LAMBERT Academic Publishing Jan 2014, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Taschenbuch
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a new augmentation method to eliminate the multicollinearity in datasets that contain several correlated predictor variables. The objective in mind is to reduce the estimation error of the regression coefficients. The main contribution of this work consists in offering a new alternative to eliminate multicollinearity in datasets by using small runs which are added in a sequential manner. The algorithm proposed will indicate the point in which the augmentations have sufficiently contributed to find the true regression model. The procedure is based on addition of new observations to the point in which an appropriate regression model can be constructed. The new information is obtained through designed experiments using the R3 algorithm as a guideline to perform the augmentations and the Ridge Trace and VIF statistic as verification tools that help to determine the point in which the correlations have been significantly reduced. The final result is a linear regression model that accurately represents the process under study. 76 pp. Englisch. N° de réf. du vendeur 9783659507038
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A Revision on Multicollinearity and Augmentation Methods
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Couverture souple
Vendeur : Books Puddle, Woodside, NY, Etats-Unis
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Etat : New. pp. 76. N° de réf. du vendeur 26127631401
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A Revision on Multicollinearity and Augmentation Methods
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Couverture souple
Vendeur : Majestic Books, Hounslow, Royaume-Uni
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Etat : New. Print on Demand pp. 76 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam. N° de réf. du vendeur 132923382
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A revision on Multicollinearity and Augmentation Methods : Multicollinearity and Augmentation Methods
Edité par
LAP LAMBERT Academic Publishing, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Taschenbuch
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a new augmentation method to eliminate the multicollinearity in datasets that contain several correlated predictor variables. The objective in mind is to reduce the estimation error of the regression coefficients. The main contribution of this work consists in offering a new alternative to eliminate multicollinearity in datasets by using small runs which are added in a sequential manner. The algorithm proposed will indicate the point in which the augmentations have sufficiently contributed to find the true regression model. The procedure is based on addition of new observations to the point in which an appropriate regression model can be constructed. The new information is obtained through designed experiments using the R3 algorithm as a guideline to perform the augmentations and the Ridge Trace and VIF statistic as verification tools that help to determine the point in which the correlations have been significantly reduced. The final result is a linear regression model that accurately represents the process under study. N° de réf. du vendeur 9783659507038
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A Revision on Multicollinearity and Augmentation Methods
Edité par
VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Couverture souple
Vendeur : Biblios, Frankfurt am main, HESSE, Allemagne
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Etat : New. PRINT ON DEMAND pp. 76. N° de réf. du vendeur 18127631395
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A revision on Multicollinearity and Augmentation Methods
Edité par
LAP LAMBERT Academic Publishing, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Couverture souple
Vendeur : moluna, Greven, Allemagne
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Etat : New. N° de réf. du vendeur 5160933
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A revision on Multicollinearity and Augmentation Methods
Edité par
LAP LAMBERT Academic Publishing Jan 2014, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Taschenbuch
Vendeur : buchversandmimpf2000, Emtmannsberg, BAYE, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book presents a new augmentation method to eliminate the multicollinearity in datasets that contain several correlated predictor variables. The objective in mind is to reduce the estimation error of the regression coefficients. The main contribution of this work consists in offering a new alternative to eliminate multicollinearity in datasets by using small runs which are added in a sequential manner. The algorithm proposed will indicate the point in which the augmentations have sufficiently contributed to find the true regression model. The procedure is based on addition of new observations to the point in which an appropriate regression model can be constructed. The new information is obtained through designed experiments using the R3 algorithm as a guideline to perform the augmentations and the Ridge Trace and VIF statistic as verification tools that help to determine the point in which the correlations have been significantly reduced. The final result is a linear regression model that accurately represents the process under study.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 76 pp. Englisch. N° de réf. du vendeur 9783659507038
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A revision on Multicollinearity and Augmentation Methods | Multicollinearity and Augmentation Methods
Edité par
LAP LAMBERT Academic Publishing, 2014
ISBN 10 : 3659507032
ISBN 13 : 9783659507038
Neuf
Taschenbuch
Vendeur : preigu, Osnabrück, Allemagne
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Taschenbuch. Etat : Neu. A revision on Multicollinearity and Augmentation Methods | Multicollinearity and Augmentation Methods | Russell Pérez González (u. a.) | Taschenbuch | 76 S. | Englisch | 2014 | LAP LAMBERT Academic Publishing | EAN 9783659507038 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 105503646
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