covariancestationarity
Covariance stationarity is a concept in time series analysis that describes the statistical properties of a time series. A time series is said to be covariance stationary if its mean, variance, and autocovariance are constant over time. This means that the statistical properties of the series do not change as time progresses.
In a covariance stationary time series, the relationship between observations at different points in time is
Covariance stationarity is a crucial assumption for many statistical models and methods, including autoregressive integrated moving
To check for covariance stationarity, various tests can be used, such as the Augmented Dickey-Fuller (ADF) test
If a time series is not covariance stationary, it may exhibit trends, seasonality, or other time-dependent patterns