3: ARMA Processes
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In this chapter autoregressive moving average processes are discussed. They play a crucial role in specifying time series models for applications. As the solutions of stochastic difference equations with constant coefficients and these processes possess a linear structure.
- 3.1: Introduction to Autoregressive Moving Average (ARMA) Processes
- In this chapter autoregressive moving average processes are discussed. They play a crucial role in specifying time series models for applications. As the solutions of stochastic difference equations with constant coefficients and these processes possess a linear structure.
- 3.3: The PACF of a Causal ARMA Process
- In this section, the partial autocorrelation function (PACF) is introduced to further assess the dependence structure of stationary processes in general and causal ARMA processes in particular.