I have time series of several variables. Just in one specific case one variable is linear combination of the rest.
I want to predict probability distribution (that is not only best estimate but estimates with probability of that happening) of future value of variables. I want to see when probability of small interval of possible outcome is high.
A priory I don't know rules of the game how variables evolve and inter-depend.
What is the tool to best do such prediction and how easy is it? Will scikit-learn do? Maybe neural networks?
ADDED based on answer:
As I've understood, time series theory data science assumes random walk, however I assume variables are at least partly moved by free will of players of the game under some a priory unknown to me constraints and goals.
Should statistical solution advised work in such case? Can data predict reversal of possible current trend?