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Synopsis
One of the many problems encountered in coming up with a multiple linear regression model is the presence of severe multicollinearity in the data set. In this work, the focus is on the mathematics of multicollinearity -- what it is, what it does to the model, how it can be detected and combated. Aside from the classical methods, artificial neural networks were also employed to combat multicollinearity. Softwares such as Statistical Package for the Social Science (SPPS) Release 7.0 and 10.0 for Windows, MATLAB version 5.3 and Stuttgart Neural Network Simulator (SNNS) version 4.1 were used to carry out the massive computations.
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About the Author
The author is an Associate Professor at De La Salle University Manila, Philippines. She obtained the degree of Doctor of Philosophy in Mathematical Sciences at the Australian National University. She was an instructor at the University of the Philippines Diliman while working on her Master's Degree in Applied Mathematics.
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- PublisherLAP LAMBERT Academic Publishing
- Publication date2011
- ISBN 10 3844327096
- ISBN 13 9783844327090
- BindingPaperback
- LanguageEnglish
- Number of pages88
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On Multicollinearity and Artificial Neural Networks
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LAP LAMBERT Academic Publishing Mai 2011, 2011
ISBN 10: 3844327096
ISBN 13: 9783844327090
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -One of the many problems encountered in coming up with a multiple linear regression model is the presence of severe multicollinearity in the data set. In this work, the focus is on the mathematics of multicollinearity -- what it is, what it does to the model, how it can be detected and combated. Aside from the classical methods, artificial neural networks were also employed to combat multicollinearity. Softwares such as Statistical Package for the Social Science (SPPS) Release 7.0 and 10.0 for Windows, MATLAB version 5.3 and Stuttgart Neural Network Simulator (SNNS) version 4.1 were used to carry out the massive computations. 88 pp. Englisch. Seller Inventory # 9783844327090
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On Multicollinearity and Artificial Neural Networks : Theory and Application
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LAP LAMBERT Academic Publishing, 2011
ISBN 10: 3844327096
ISBN 13: 9783844327090
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Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - One of the many problems encountered in coming up with a multiple linear regression model is the presence of severe multicollinearity in the data set. In this work, the focus is on the mathematics of multicollinearity -- what it is, what it does to the model, how it can be detected and combated. Aside from the classical methods, artificial neural networks were also employed to combat multicollinearity. Softwares such as Statistical Package for the Social Science (SPPS) Release 7.0 and 10.0 for Windows, MATLAB version 5.3 and Stuttgart Neural Network Simulator (SNNS) version 4.1 were used to carry out the massive computations. Seller Inventory # 9783844327090
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On Multicollinearity and Artificial Neural Networks
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ISBN 10: 3844327096
ISBN 13: 9783844327090
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Carpio Kristine JoyThe author is an Associate Professor at De La Salle University Manila, Philippines. She obtained the degree of Doctor of Philosophy in Mathematical Sciences at the Australian National University. She was an in. Seller Inventory # 5473112
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On Multicollinearity and Artificial Neural Networks: Theory and Application
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ISBN 10: 3844327096
ISBN 13: 9783844327090
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