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Estimate the autocorrelation function (ACF) for an autoregression

What if you need to estimate the autocorrelation function from your data? To do so, you'll need the acf() command, which estimates autocorrelation by exploring lags in your data. By default, this command generates a plot of the relationship between the current observation and lags extending backwards.

In this exercise, you'll use the acf() command to estimate the autocorrelation function for three new simulated AR series (x, y, and z). These objects have slope parameters 0.5, 0.9, and -0.75, respectively, and are shown in the adjoining figure.

Cet exercice fait partie du cours

<cours>Time Series Analysis in R</cours>
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Instructions de l’exercice

  • Use three calls to acf() to calculate the ACF for x, y, and z, respectively.

Exercice interactif pratique

Essayez cet exercice en complétant ce code d’exemple.

# Calculate the ACF for x
acf(___)

# Calculate the ACF for y


# Calculate the ACF for z

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