  This paper discusses desirable properties of forecasting models in production
systems. It then develops a family of models which are designed to satisfy
these properties: highly customizable to capture complex patterns; accommodates
a large variety of objectives; has interpretable components; produces robust
results; has automatic changepoint detection for trend and seasonality; and
runs fast -- making it a good choice for reliable and scalable production
systems. The model allows for seasonality at various time scales,
events/holidays, and change points in trend and seasonality. The volatility is
fitted separately to maintain flexibility and speed and is allowed to be a
function of specified features.
