Machine Learning, Time Series Analysis, Support Vector Machine, Gaussian Process, Kernel Methods.
random variable that can generate any possible outcome is wrong. The same goes for stochastic processes. So long as a diffusion can generate any path over a bounded input space, it is a valid time series model or functional prior! As it turns out, the space of paths of the simple stationary