Introduction to Time Series & Prediction

Harvard FAS

Introduction to time series models and forecasting. Introduction to classical time series model: autoregressive, moving average, ARIMA models. Some concepts from stochastic processes: martingales, stationarity, Gaussian processes, Brownian motions, ergodic theorems. Some aspects of advanced time series: hidden Markov models, state space models, filtering, smoothing, Kalman filters, sequential Monte Carlo methods.