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.
Deze oefening maakt deel uit van de cursus
Time Series Analysis in R
Oefeninstructies
- Use three calls to
acf()to estimate the autocorrelation functions forx,y, andz, respectively.
Praktische interactieve oefening
Probeer deze oefening eens door deze voorbeeldcode in te vullen.
# Calculate ACF for x
acf(___)
# Calculate ACF for y
# Calculate ACF for z