A decay pattern refers to the way in which the correlation between observations in a time series decreases as the time lag increases. It is a crucial aspect when analyzing the autocorrelation function (ACF) because it helps to identify the presence of a relationship over time, providing insights into the structure and predictability of the data. Understanding decay patterns allows analysts to determine if a time series is stationary or if it exhibits trends or seasonality.
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