Statistics for stochastic processes
Estimation and inference of the discrete and continuous stochastic processes have always been considered as a challenging problem in statistics, since one has to take time dependence into account. Here various methods can be used especially parametric methods for time series, nonparametric procedures for diffusion processes and computational algorithms like MCMC. The application areas are very broad, ranging from financial modelling and engineering to building weather forecasts and energy economics.
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