microcovariance
Microcovariance is a statistical concept used to measure the linear relationship between two variables within a smaller, more localized context, rather than across an entire dataset. Unlike traditional covariance which considers all data points, microcovariance focuses on a specific subset or a moving window of data. This allows for the detection of relationships that may exist only within certain segments of the data or that change over time.
The calculation of microcovariance involves selecting a subset of the data, typically a contiguous block or
The interpretation of microcovariance is similar to that of regular covariance. A positive microcovariance indicates that