The Decomposition Issue of a Time Series in the Forecasting Process

Decomposition of time series is the estimate and extraction of deterministic part of the series - trend, cyclical and seasonal fluctuations in the hope that the rest of the data, that is, theoretically, a random variable will be stationary random process. During the process of predicting the time series elements affects significantly on the determination of the future values, which are characterized by a low forecast error. Therefore, the purpose of this article is to identify the elements of the time series decomposition and to determine the extent to which they affect the forecasting process. Problems that often appear when you run the forecast and methods of building models and forecasts based on time series will be presented. Observations will be described on the basis of nonparametric time series modeling.