In probability theory and statistics, a Hawkes process, named after Alan G. Hawkes, is a kind of self-exciting point process.
where the infinitesimal probability of an arrival during the time interval
is the intensity of an underlying Poisson process.
The first arrival occurs at time
and immediately after that, the intensity becomes
μ ( t ) + ϕ ( t −
of the second arrival the intensity jumps to
μ ( t ) + ϕ ( t −
independent processes with intensities
μ ( t ) , ϕ ( t −
The arrivals in the process whose intensity is
are the "daughters" of the arrival at time
is the average number of daughters of each arrival and is called the branching ratio.
Thus viewing some arrivals as descendants of earlier arrivals, we have a Galton–Watson branching process.
The number of such descendants is finite with probability 1 if branching ratio is 1 or less.
If the branching ratio is more than 1, then each arrival has positive probability of having infinitely many descendants.
Hawkes processes are used for statistical modeling of events in mathematical finance,[3] epidemiology,[4] earthquake seismology,[5] and other fields in which a random event exhibits self-exciting behavior.