Time Series Analysis

3 credits · Undergraduate Programs

Description reads as: An introduction to the theory and tools to conduct time series analysis, with the emphasis on modeling and forecasting using a software. Stationarity, white noise, autocorrelation, partial autocorrelation, and linear predictor. Stationary ARIMA models, seasonality and trends. Model fitting, diagnostics and forecasting. Additional topics may include state space models, spectral analysis of time series, and GARCH models. Prerequisite(s): Statistics 429.