A Metric Space for Point Process Excitations
- URL: http://arxiv.org/abs/2005.02515v4
- Date: Sat, 23 Apr 2022 21:04:58 GMT
- Title: A Metric Space for Point Process Excitations
- Authors: Myrl G. Marmarelis, Greg Ver Steeg, Aram Galstyan
- Abstract summary: A Hawkes process enables self- and cross-excitations through a triggering matrix.
We propose a Hidden Hawkes Geometry model to uncover the hidden geometry between event excitations.
The low dimensionality of the embedding regularizes the structure of the inferred interactions.
- Score: 30.64702411507204
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A multivariate Hawkes process enables self- and cross-excitations through a
triggering matrix that behaves like an asymmetrical covariance structure,
characterizing pairwise interactions between the event types. Full-rank
estimation of all interactions is often infeasible in empirical settings.
Models that specialize on a spatiotemporal application alleviate this obstacle
by exploiting spatial locality, allowing the dyadic relationships between
events to depend only on separation in time and relative distances in real
Euclidean space. Here we generalize this framework to any multivariate Hawkes
process, and harness it as a vessel for embedding arbitrary event types in a
hidden metric space. Specifically, we propose a Hidden Hawkes Geometry (HHG)
model to uncover the hidden geometry between event excitations in a
multivariate point process. The low dimensionality of the embedding regularizes
the structure of the inferred interactions. We develop a number of estimators
and validate the model by conducting several experiments. In particular, we
investigate regional infectivity dynamics of COVID-19 in an early South Korean
record and recent Los Angeles confirmed cases. By additionally performing
synthetic experiments on short records as well as explorations into options
markets and the Ebola epidemic, we demonstrate that learning the embedding
alongside a point process uncovers salient interactions in a broad range of
applications.
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