TIME SERIES ANALYSIS
These four exercises come from the Time Series Analysis course at DTU. Topics include stochastic processes, random walks and simulations of them, Auto-Regressive and Moving-Average (ARIMA) models as well as predicting with multiple predictor variables (MARIMA models) and Kalman Filters. These time series methods are used to predict apartment prices in Lyngby, DK, NOx emissions in Copenhagen, DK, as well as future GPS measurements taken from an individual's cell phone during a morning jog. For more specific info please read the assignment pdf files.