A linear forecasting model and its application to economic data

We present a forecasting model based on fuzzy pattern recognition and weighted linear regression. In this model fuzzy pattern recognition is used to find homogeneous fuzzy classes in a heterogeneous data set. It is assumed that the classes represent typical situations. For each class a weighted regression analysis is conducted. The forecasting results obtained by the class regression analysis are aggregated to obtain the ‘overall’ estimation of the regression model. We apply the model to the forecasting of economic data of the USA.