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.