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School of Economics and Finance, Queen Mary, University of London >
Working Paper Series, School of Economics and Finance, Queen Mary, University of London >
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http://hdl.handle.net/10419/62937
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| Title: | | Boosting estimation of RBF neural networks for dependent data  |
| Authors: | | Kapetanios, George Blake, Andrew P. |
| Issue Date: | | 2007 |
| Series/Report no.: | | Working Paper, Department of Economics, Queen Mary, University of London 588 |
| Abstract: | | This paper develops theoretical results for the estimation of radial basis function neural network specifications, for dependent data, that do not require iterative estimation techniques. Use of the properties of regression based boosting algorithms is made. Both consistency and rate results are derived. An application to nonparametric specification testing illustrates the usefulness of the results. |
| Subjects: | | Neural Networks, Boosting |
| JEL: | | C12 C13 C22 |
| Document Type: | | Working Paper |
| Appears in Collections: | | Working Paper Series, School of Economics and Finance, Queen Mary, University of London
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