Work

Estimation of spatiotemporal poisson processes with missing data

Year: 2026

Type: article

Abstract: We consider models for spatiotemporal Poisson processes with some missing location data. We discuss four models that make provision for missing location data, and their estimation. The corresponding code is available on GitHub as an extension of LASPATED at https://github.com/vguigues/LASPATED in the Missing_Data subdirectory. We tested our models using the process of emergency call arrivals to an emergency medical service, where the emergency reports often omit the location of the emergency. We show the difference made by using models that make provision for missing location data. Finally, we show how to develop models that deal with missing data of time stamp.

Source: Scientific Reports

DOI: 10.1038/s41598-026-46520-y

Authors: Vincent Guigues, Anton Kleywegt, Victor Hugo Nascimento, Lucas Rafael de Andrade

Institutions: Fundação Getulio Vargas, Georgia Institute of Technology

Language: English

Topic: Point processes and geometric inequalities

Subfield: Applied Mathematics

Field: Mathematics

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,690

OpenAlex ID: W7155499353