Autocorrelation


Autocorrelation is a statistical method used to measure the similarity between a time series and a lagged version of itself over successive time intervals. It is a measure of the degree of similarity between a given time series and a lagged version of itself over successive time intervals. Autocorrelation is used to identify patterns in the data that repeat over time, and it is commonly used in time series analysis to identify trends and seasonality. The autocorrelation function (ACF) is a plot of the autocorrelation coefficient for each lagged interval, and it is used to determine the optimal lag for forecasting future values of the time series.


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