I am trying to understand the underlying fundamental/statistical differences between vector autoregression models and Facebook's Prophet, with regards to multivariate time series forecasting.
I am very new to time series forecasting, but I am really looking to understand the differences between these models in terms of how they approach fitting a trend and forecasting future values. Most comparisons I can find online are in terms of their actual performance differences, that is not what I am looking for.
This is all very new so any pointers to resources which explain how Prophet and VAR work – for someone without a deep mathematical background – would be excellent, and then I can derive the answer myself from there. I cannot find very much about what Prophet really is, beyond the description.
My experience is in machine learning methods as opposed to time series forecasting, so I would appreciate any explanation which accounts for my very basic subject matter knowledge.