- Introduction and background review.

- Stationary stochastic processes.

Click here for the file I used to plot the spectrum of AR(1) and MA(1).

- Linear stationary and nonstationary models.

Click here for a function to generate ARIMA process.

Click here for a plotting code for the stationary region of AR(2).

Click here for a function to calculate the spectrum of ARMA processes.

Click here for a function implementing the Durbin-Levinson recursion.

Click here for a function implementing the moment estimates for ARMA model.

Click psi.arma.R and pi.arma.R for functions calculating the psi and pi coefficients.

- Model estimation and model checking tools.

- Forecasting.

Click for forecast.arma.R and fweight.arma.R.

Click here for some algebra concerning the forecasting weights.

Click here for some algebra concerning a few examples.

- State space models.

Click here for some algebra concerning the state space representation of ARIMA models.

Click here for a diagram and some algebra concerning Kalman filter.

Click here for some algebra concerning multi-step prediction using Kalman filter.

Click here for some algebra of Slide 11.

Click here and here for some algebra of Slide 12.

- Seasonal models.

Click here for some ACF calculation.

- Spectral Analysis.

Click here for some DFT facts.

Click here and here for some periodogram facts.

Click here for some insights and details concerning lag window estimates.

Click here for some examples of Daniel windows.

- Transfer function models.

Click here and here for some details of the example.

- ARCH and GARCH models.

Click here for some algebra.