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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.

Questo esercizio fa parte del corso

Time Series Analysis in R

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Istruzioni dell'esercizio

  • Use three calls to acf() to estimate the autocorrelation functions for x, y, and z, respectively.

Esercizio pratico interattivo

Prova a risolvere questo esercizio completando il codice di esempio.

# Calculate ACF for x
acf(___)

# Calculate ACF for y


# Calculate ACF for z

Modifica ed esegui il codice