API Reference

Univariate Hawkes Processes

Multivariate Hawkes Processes

Multivariate Hawkes processes are those in which event occurrences assume discrete marks from a finite set of cardinality K. Analogously, we can think of K distinct Hawkes processes running, that not only self-excite, but also excite other processes (i.e. are mutually exciting).

Poisson Processes

For sake of completeness and comparability, we provide temporal Poisson processes (and a Bayesian variant) implementing the PointProcess interface, just like Hawkes processes.

The same functionality as for Hawkes; such as computing log likelihoods (or posterior potentials), maximum likelihood (or MAP) estimates of parameters, and posterior sampling are implemented. Note that due to the well-known complete randomness property of Poisson processes, and also the use of a conjugate prior for the Bayesian case, these methods are implemented just in a few lines of code.