I would like to model the effect the effect of an exogenous regressor (let's say weather) on a time series (let's say of sales at beach resort X for the example). However, I have insufficient data on the sales at beach resort X to properly train the model, the time series is too short.
Is there an approach to use the data from several time series of weather and sales at other resorts to train the model on the effect of weather? How can this be implemented in python?
Thanks
