Counting process Created 2026-09-24 Updated 2026-11-05
A counting process records accumulated events. It is a nonnegative integer-valued Stochastic process , usually adapted and càdlàg, with and nondecreasing sample paths. Nonexplosion means at every finite time. In a simple counting process, every jump is one; broader counting conventions also allow several events at the same instant.
A rate- Poisson process has independent stationary increments, mean and variance . A one-event process , with , instead records whether its single event has occurred. It is a counting process without the Poisson process's unrestricted repeated arrivals.
The path is the observed count. A counting-process intensity describes its conditional event rate, and a compensator accumulates that predictable rate or, more generally, a predictable event measure. These objects are not the same: the count has integer jumps, whereas a continuous compensator can increase between observed events. In Survival analysis, the one-event convention naturally combines a Hazard function with an at-risk process.
Simple counting process 2026-11-05
A simple counting process counts individual events without simultaneous multiplicities. In the usual convention, , its sample paths are nondecreasing, integer-valued and càdlàg, every jump discontinuity has size one, and is finite for every finite . Equivalently,
where the finite arrival times are strictly increasing and have no finite accumulation point.
Simplicity specifies how arrivals are counted; it does not assert independent increments or a Poisson distribution. Deterministic arrivals at times give a simple counting process, as does a renewal process with strictly positive independent and identically distributed interarrival times. A system that records an entire batch as several events at exactly the same time can have a jump discontinuity larger than one and therefore is not simple. The Poisson process adds particular increment laws to these counting-path properties.