autokorrelációra
Autokorrelációra, often translated as autocorrelation, is a statistical concept that measures the similarity between a time series and a lagged version of itself. It essentially quantifies how correlated a sequence of data points is with its past values. The autocorrelation function (ACF) is a common tool used to visualize and analyze this relationship. The ACF plots the correlation coefficient against different lags, where a lag of one means comparing a data point to the one immediately preceding it, a lag of two compares it to the value two steps back, and so on.
High positive autocorrelation indicates that a high value in the series is likely to be followed by
Autocorrelation is a fundamental concept in time series analysis and is crucial for understanding the underlying