Applied Time Series Analysis

Graduate course, Rutgers University, 2020


An introduction to statistical methodologies for time series and their applications. Stationary processes, estimation of trend, linear processes, ARMA and ARIMA models, model building, diagnostics, and forecasting. Select advanced time series topics including seasonal models, nonlinear models, state space models, and spectral analysis of time series. Data analysis with computational software is emphasized.


  • Cryer, J. D., & Chan, K. S. (2008). Time series analysis: with applications in R. Springer Science & Business Media.