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Forecasting time series considering holidays and rare events requires a special approach, as such events can significantly influence data behavior but occur irregularly.

Features:

• Adding additional features: indicators for holidays, weekends, and rare events should be added to the model so it can account for their influence.
• Nonlinear and unpredictable effects: the impact of holidays can vary from year to year, complicating modeling.
• Lack of data on rare events: few examples for training, which reduces forecast quality.
• Use of specialized models: for example, Facebook's Prophet, which can consider seasonality and holidays.

Example: when forecasting sales in a store, it should be considered that sales can sharply increase or decrease on holidays, and the model should reflect this through additional variables or special seasonal components.