Table 4.

Some Strengths and Weaknesses of the Individual Models.

Model	Strengths	Weaknesses
ARIMA	Few parameters, interpretable, short-term forecasts	Requires stationary data, unusual trends.
Prophet	Outliers, Missing data, Speed, Robust, Powerful, Strong seasonal effects, Long forecasting, Automatic.	No readily known weaknesses
Holt-Winters ES	Strong and accurate forecasting (short-term), favors recent data samples, requires few data points, straightforward implementation.	Lagged forecasts.