ACF in R interpretation

1. How do you interpret ACF values?
2. How do you explain an ACF plot?
3. What does ACF mean in R?

How do you interpret ACF values?

The ACF shows the correlation between the time series and its own lagged values. It represents a correlation coefficient between the series and its past values. For instance, ACF at lag 3 is calculated as the correlation between the series (Y_t) and the same series lagged by 3 time periods (Y_t-3).

How do you explain an ACF plot?

ACF plot is a bar chart of coefficients of correlation between a time series and it lagged values. Simply stated: ACF explains how the present value of a given time series is correlated with the past (1-unit past, 2-unit past, …, n-unit past) values.

What does ACF mean in R?

Description. The function acf computes (and by default plots) estimates of the autocovariance or autocorrelation function. Function pacf is the function used for the partial autocorrelations. Function ccf computes the cross-correlation or cross-covariance of two univariate series.