Modeling and Forecasting of the Temporal Series By the Sum of Logistic, Linear and Harmonic Components on the Basis of ARMA-model
The article views a new approach towards modeling and forecasting of temporal series by the sum of logistic, linear and harmonic components on the basis of a parametrical model of the autoregression of the moving average. For the main logistic trend we used the poorly known Ramsey function which is close to Verhoulst function by its view and parameters. Nevertheless, it has got more plain analytical expression. We have performed the research of the model precision on test samples as well as upon real data. The acquired results showed high precision of modeling and forecasting within the wide diapason of meanings of the model parameters, coordination "noise - signal", and testing on real data showed the possibility to use the model for different economical processes.