Exercise

Simulating ARMA models

As we saw in the video, any stationary time series can be written as a linear combination of white noise. In addition, any ARMA model has this form, so it is a good choice for modeling stationary time series.

R provides a simple function called arima.sim() to generate data from an ARMA model. For example, the syntax for generating 100 observations from an MA(1) with parameter .9 is arima.sim(model = list(order = c(0, 0, 1), ma = .9 ), n = 100). You can also use order = c(0, 0, 0) to generate white noise.

In this exercise, you will generate data from various ARMA models. For each command, generate 200 observations and plot the result.

Instructions

100 XP
  • Use arima.sim() and plot() to generate and plot white noise.
  • Use arima.sim() and plot() to generate and plot an MA(1) with parameter .9.
  • Use arima.sim() and plot() to generate and plot an AR(2) with parameters 1.5 and -.75.