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In recent research, we have automated the feature identification process using simple statistical approaches. Consequently, time commitment to feature identification has dropped to under one minute per series without consequential decline in forecast accuracy.
Through extensive sensitivity analyses, we have found that causal forces are one of the key features of RBF. This feature represents the cumulative directional effect of the factors that influence the trends in a time series.
Features of Time Series. Functional form Multiplicative Additive Expected pattern of the trend of the series. Cycles expected Cycles expected Regular movement of the series about the basic trend. Forecast horizon Forecast horizon Horizon for which forecasts are being made. Seasonality Seasonality Whether seasonality is present in the series.
Suspicious pattern Series that show a substantial change in recent pattern. Unstable recent trend Series that show marked changes in recent trend pattern. Outliers present Isolated observation near a 2 std. Recent run not long The last six period-to-period movements are not in same direction.