If I use fit predict interface on 100 timeseries, what are the saved weights if I pickle the StatsForecast object?

Hey @Kevin Kho! The

fit

method stores a

fitted_

attribute containing the fitted models for each time series. Each fitted model is different. For example, the naive model stores the last time series observation, while Arima stores other objects required for forecasting. Currently, we do not have the functionality to use a different time series for forecasting. The

predict

method only receives the horizon to forecast, so if the fitted model is saved, the forecasts produced by it will be the same each time

predict

is called. We are working on adding the functionality to use new data. For the moment, we recommend using the forecast method.

Ah how does it work then for exogenous variables? What if

fit()

has one? How is it supplied to predict?