Use multiple time-series to train model

Question

Is there any way to use multiple time-series to train one model and use this model for predictions given a new time-series as an input? It is rather a theoretical question but did not know where else to post it.

Answer 1

It's theoretically possible, nevertheless every time-series has it's own components about seasonality, stationarity, frequency. (In case you talk about mixing series).

I've seen some work using wavelets-decomposition, deep-learning, time-series and uses several datasets and weights to train the model. But the time-series are similar, same metric different times (aka Temperature in a city from 2000-2001, 2005-2007).

I found some library called darts