Hyndman-Khandakar algorithm

The Hyndman-Khandakar algorithm is a method used to automatically select the best time series forecasting model. It combines statistical techniques to identify the most suitable model (like ARIMA) by testing different configurations, ensuring the chosen model captures patterns such as trends or seasonality. The algorithm fine-tunes parameters to optimize forecast accuracy while controlling complexity, helping analysts generate reliable predictions without manual trial-and-error. Essentially, it streamlines the process of finding an effective forecasting model through an automated and systematic approach.