It is a standard historical benchmark in the forecasting community and is often included in modern research packages like the tscompdata R package on GitHub.
The NN3 competition was designed to evaluate how modern neural network (NN) and computational intelligence (CI) methods compare to traditional statistical benchmarks like those used in the M3 competition. Composition: nn3.zip
111 monthly time series, including the 11 from the reduced set. It is a standard historical benchmark in the
The historical data is typically provided in vertical columns of varying lengths. The historical data is typically provided in vertical
Contestants were traditionally required to forecast 18 points into the future.
The series vary in length (68 to 144 observations) and include seasonal, non-seasonal, and "difficult" patterns with outliers and structural breaks. Key Strengths
For modern use, researchers often access these files through the NN3 Official Website or data science repositories like Kaggle . Critical Reception