Normally the method for dealing with 'time series' is really just finding ways to turn a non-stationary distribution into a stationary distribution, where you can then apply classic statistical methods on them. So you're just finding ways to factor out the time component in the data so you can use the standard non-time sensitive regression models on the transformed data.
I don't think it's untill you get to the NN based models that they start treating time as a first-class component in the model.
* If I'm wrong please explain why instead of downvoting
I don't think it's untill you get to the NN based models that they start treating time as a first-class component in the model.
* If I'm wrong please explain why instead of downvoting