Initialization Methods for Multiple Seasonal Holt–Winters Forecasting Models

• Main Authors: Oscar Trull, Juan Carlos García-Díaz, Alicia Troncoso
• Format: Article
• Language: English
• Published: MDPI AG 2020-02-01
• Series: Mathematics
• Subjects: forecasting; multiple seasonal periods; holt–winters, initialization
• Online Access: https://www.mdpi.com/2227-7390/8/2/268

The Holt−Winters models are one of the most popular forecasting algorithms. As well-known, these models are recursive and thus, an initialization value is needed to feed the model, being that a proper initialization of the Holt−Winters models is crucial for obtaining a good accuracy of the predictions. Moreover, the introduction of multiple seasonal Holt−Winters models requires a new development of methods for seed initialization and obtaining initial values. This work proposes new initialization methods based on the adaptation of the traditional methods developed for a single seasonality in order to include multiple seasonalities. Thus, new methods to initialize the level, trend, and seasonality in multiple seasonal Holt−Winters models are presented. These new methods are tested with an application for electricity demand in Spain and analyzed for their impact on the accuracy of forecasts. As a consequence of the analysis carried out, which initialization method to use for the level, trend, and seasonality in multiple seasonal Holt−Winters models with an additive and multiplicative trend is provided.