Temporal pattern
This is the landing page for everything related to the temporal pattern of your process.
There are characteristic ways in which a process may vary over time. We can characterize this variation by lasting changes, reversible changes, or no changes (i.e., mere fluctuations). For example, it could switch between regimes or follow a growth curve. The temporal lens of your study should be devised to capture the expected pattern over time. This also requires you to think about the timescale at which your process operates.
Below we have specified multiple articles that help you consider the temporal pattern of your process.
Think more about temporal patterns
Your theory should cover how you expect the process to fluctuate or change over time.
- [Growth curves]
- Regimes-switching processes
- Event-relations
- [Autoregressive processes]
- [Seasonality]
- Stationarity versus non-stationarity
The coverage of your process relies on the number and timing of your measurement occasions.
- Time span, process coverage, and granularity
- Occasions
- [Multiple timescales]