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Articles by Dursun Aydin
Total Records ( 2 ) for Dursun Aydin
  Dursun Aydin and M. Seref Tuzemen
  This study presented a comparative study of the different smoothing parameter selection methods. The parameter selection problem has been examined in respect to a smoothing spline implementation in predicting nonparametric regression models. For this purpose, a simulation experiment has been carried out by using a program written in MATLAB 6.5. The simulation experiment provides a comparison of the six different selection methods. In this context, 500 replications have been carried out in simulation for sample sets with different sizes. Thus, the empirical performances of the six selection criteria have been investigated and the suitable selection criteria are obtained for an optimum parameter selection.
  Dursun Aydin
  In this study, we will investigate and compare the performance of some forecasting methods for time series with both trend and seasonal patterns. The forecasting performance has been compared with six models and these include: Auto Regressive Integrated Moving Average (ARIMA), Smoothing Spline Model (SSM), Regression Spline Model (RSM), Additive Regression Model (ARM), Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) network models. The SSM, RSM and ARM are called as non-parametric regression models, whereas MLP and RBF are known as artificial neural network models. For these models, we conducted a comparison based on actual data sets, the number of tourist coming to Turkey. The empirical results obtained have shown that MLP performed better than other models. In addition, the SSM can be considered as an alternative to MLP.
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