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Investigates missing location data impacts on spatiotemporal Poisson processes, suggesting model improvements.
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.
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Guigues et al. (2026) studied this question.
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