Boosting estimation of RBF neural networks for dependent data - George Kapetanios; Andrew P. Blake (Queen Mary University of London, Department of Economics, 2007)
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.
Keywords: C12; C13; C22; 330; Neural Networks; Boosting; Neuronale Netze; Nichtparametrisches Verfahren; Sch\~AƒÂtztheorie