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?
predicting probability distribution for time series
predictive modeling;time series;scikit learn;probability