Autokovarianssien
Autokovarianssien, often translated as autocovariance, is a statistical measure that quantifies the similarity between a time series and a lagged version of itself. In essence, it describes how much two points in a time series, separated by a certain time interval, tend to vary together. If the autocovariance is high and positive, it suggests that when one value is high, the value at the lagged time point is also likely to be high, and vice-versa. A high negative autocovariance implies that when one value is high, the value at the lagged time point is likely to be low.
The autocovariance function (ACF) plots the autocovariance at different lags. This function is crucial in time
Autocovariance is calculated by taking the covariance between the time series values at time t and the