Poissonhypyt
Poissonhypyt is a theoretical construct in probability and statistics that describes a class of point processes extending the classical Poisson process by allowing the event rate to vary randomly over time. The name is used in a minority of literature and is sometimes treated as a synonym or alias for doubly stochastic Poisson processes, also known as Cox processes.
In the Poissonhypyt framework, the counting process N(t) is conditionally Poisson given a stochastic intensity Λ(t).
Metrics and properties: The unconditional distribution of counts is typically not Poisson; the process exhibits overdispersion
Estimation and inference: Common approaches include likelihood-based methods with data augmentation, Bayesian inference via MCMC or
Applications: The Poissonhypyt model is used to describe bursty event data in telecommunications, finance (trade counts),
Status and terminology: Poissonhypyt is not universally standardized and is sometimes superseded by the broader term