A rolling window is a moving subset of data points that ends at the current timestamp (inclusive) and spans a specified duration (window size). As new data points are added, old points fall out of the window if they are outside the specified duration.
Rolling windows are commonly used for smoothing data, detecting trends, and reducing noise in time series analysis.
This is a discriminator type and does not contain any fields. Instead, it is a union of of the models listed below.
This discriminator class uses the type field to differentiate between classes.
| Class | Value |
|---|---|
| PreciseDuration | duration |
| RollingAggregateWindowPoints | pointsCount |