autocorrelation function

The autocorrelation function measures how a variable's current value is related to its past values over time. It helps identify patterns, trends, or cycles within data by comparing observations at different time intervals. For instance, in weather data, autocorrelation can show how today’s temperature is similar to temperatures from previous days. A strong autocorrelation indicates that past values significantly influence the current state, while a weak correlation suggests that past values have little impact. This analysis is valuable in fields like finance, economics, and environmental science for forecasting and understanding temporal relationships.