Temporal Point Process

A Temporal Point Process is a point process that models a temporal process.

• Context:
  • It can be represented by a Temporal Point Process Dataset, such as a time-series of binary events.
• See: Spatial Point Process.

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References

2017

• Uri Eden. (2017). http://www.stat.columbia.edu/~liam/teaching/neurostat-fall17/uri-eden-point-process-notes.pdf Chapter 2: Introduction to Point Pr"[ocesses]."
  • … A temporal point process is a stochastic, or random, process composed of a time-series of binary events that occur in continuous time (Daley and Vere-Jones, 2003). They are used to describe data that are localized at a finite set of time points. As opposed to continuous-valued processes, which can take on any of countless values at each point in time, a point process can take on only one of two possible values, indicating whether or not an event occurs at that time. In a sense, this makes the probability models used to describe point process data relatively easy to express mathematically. However, point process data are often inappropriately analyzed, because most standard signal-processing techniques are designed primarily for continuous-valued data. A fundamental understanding of the probability theory of point processes is vital for the proper analysis of point process data. ...

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