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With high variabilty data, how do you choose between ETS and ARIMA?

Ray McLean
Ray McLean Workflow Optimization Thought Leader/Data ScientistFounding Analyst | Scholar ✭✭

Accuracy measures are often interpretive making it hard to choose which model is the best. The rule of thumb is to have lowest numbers possible associated with percent of error. With that said, numbers sometimes flip between models (ETS and ARIMA). Looking for opinions on the Root Mean Squared Error (RMSE) - Mean Absolute Error (AMA); the Mean Percentage Error (MPE), the Mean Absolute Percentage Error (MAPE), and the Mean Absolute Scaled Error (MASE). The various errors can be better in between models. What is your process to decide which model you choose? (this is with consideration that historical data aligns with trends, seasonality and moving averages).

Any thoughts?