Could anyone provide some guidance on when to use the function SEASONAL_LINEAR_REGRESSION over FORECAST_ETS? In our specific case we have a metric with a yearly seasonality and the overall trend for the metric is going slightly downwards. We would like to use our actuals data to automatically calculate values for all forecast months. I can see that both functions gives me reasonable values for my forecast, but FORECAST_ETS gives me a clearer trend downwards while SEASONAL_LINEAR_REGRESSION gives me more flat forecast.

So my question is really, which one would make most sense to use in our case and why?

**Best answer by Thu Mai**