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Mastering Predictive Analytics with R by Rui Miguel Forte

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Stationary time series models

In this section, we will describe a few stationary time series models. As we will see, these can be used to model a number of real-world processes.

Moving average models

A moving average (MA) process is a stochastic process in which the random variable at time step t is a linear combination of the most recent (in time) terms of a white noise process. Concretely, we can write this in an equation as follows:

Moving average models

In the previous equation, and henceforth, we will assume that the e terms are white noise random variables with mean 0 and variance σw2. We can describe a moving average process in an equivalent way by making use of ...

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