Improving the Global Fitting Method on Non-Linear Time Series Analysis

In this paper, we are concerned with improving the forecast capabilities of the Global approach to Time Series. We assume that the normal techniques of Global mapping are applied, the noise reduction is performed, etc. Then, using the mathematical foundations behind such approaches, we propose a method that, without a great computational cost, greatly increase the accuracy of the corresponding forecasting.