The autocorrelation function looks at how closely related pairs of observations in a time series are when they are separated by a fixed number of time intervals. This helps in understanding patterns in the data and is important for modeling time series. The researchers defined the autocorrelation function and the partial autocorrelation function, and explained how to estimate them.