autokorrellasjonen
Autokorrellasjon, also known as autocorrelation, is a statistical concept that measures the degree of similarity between a given time series and a lagged version of itself over successive time intervals. It quantifies the extent to which current values of a data set are correlated with past values, providing insight into the internal structure or pattern of the data.
Autokorrellasjon is widely used in fields such as signal processing, economics, meteorology, and finance to identify
Mathematically, autocorrelation is calculated as the correlation coefficient between the original series and a lagged version
An important aspect of autocorrelation is its potential to violate assumptions of independence in many statistical
Understanding autocorrelation helps in model selection and in refining forecasts by accounting for intrinsic dependencies within