Exercise

# Estimate the autocorrelation function (ACF) for a moving average

Now that you've simulated some MA data using the `arima.sim()`

command, you may want to estimate the autocorrelation functions (ACF) for your data. As in the previous chapter, you can use the `acf()`

command to generate plots of the autocorrelation in your MA data.

In this exercise, you'll use `acf()`

to estimate the ACF for three simulated MA series, `x`

, `y`

, and `z`

. These series have slope parameters of 0.4, 0.9, and -0.75, respectively, and are shown in the figure on the right.

Instructions

**100 XP**

- Use three calls to
`acf()`

to estimate the autocorrelation functions for`x`

,`y`

, and`z`

, respectively.