Narayanan, Santhosh;
Kosmidis, Ioannis;
Dellaportas, Petros;
(2021)
Flexible marked spatio-temporal point processes with applications to event sequences from association football.
arXiv.org: Ithaca (NY), USA.
Preview |
Text
Dellaportas_Flexible marked spatio-temporal point processes with applications to event sequences from association football_pre-print.pdf Download (1MB) | Preview |
Abstract
We develop a new family of marked point processes by focusing the characteristic properties of marked Hawkes processes exclusively to the space of marks, providing the freedom to specify a different model for the occurrence times. This is possible through the decomposition of the joint distribution of marks and times that allows to separately specify the conditional distribution of marks given the filtration of the process and the current time. We develop a Bayesian framework for the inference and prediction from this family of marked point processes that can naturally accommodate process and point-specific covariate information to drive cross-excitations, offering wide flexibility and applicability in the modelling of real-world processes. The framework is used here for the modelling of in-game event sequences from association football, resulting not only in inferences about previously unquantified characteristics of game dynamics and extraction of event-specific team abilities, but also in predictions for the occurrence of events of interest, such as goals, corners or fouls in a specified interval of time.
| Type: | Working / discussion paper |
|---|---|
| Title: | Flexible marked spatio-temporal point processes with applications to event sequences from association football |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | https://doi.org/10.48550/arXiv.2103.04647 |
| Language: | English |
| Additional information: | © The Author 2022. Original content in this paper is licensed under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) Licence (https://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Bayesian inference; Hamiltonian Monte Carlo; team abilities; branching structure |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Statistical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10159265 |
Archive Staff Only
 |
View Item |
