What is the best model for time series forecasting?

Multistep-ahead prediction is the task of predicting a sequence of values in a time series . A typical approach, known as multi-stage prediction, is to apply a predictive model step-by-step and use the predicted value of the current time step to determine its value in the next time step.

One-step ahead forecasts are computed sequentially for each data point by using computed level and trend states for the current point, and seasonal states for the last seasonal period . Forecast error is computed by subtracting forecast value at the previous point from the observed value at the current point.

Time series forecasting occurs when you make scientific predictions based on historical time stamped data . It involves building models through historical analysis and using them to make observations and drive future strategic decision-making.

The forecast horizon is the length of time into the future for which forecasts are to be prepared . These generally vary from short-term forecasting horizons (less than three months) to long-term horizons (more than two years).