Short proof of the conditioning property for multi-dimensional Poisson point processes

Fuente: arXiv
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1. Verfasser: Lanchier, Nicolas
Format: Preprint
Veröffentlicht: 2025
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author Lanchier, Nicolas
author_facet Lanchier, Nicolas
contents Poisson processes and one-dimensional Poisson point processes satisfy three main properties: superposition, thinning, and conditioning. The proof of the first two relies on basic estimates involving the Poisson distribution that are also true for multi-dimensional Poisson point processes. In contrast, the proof of conditioning uses that the distances between consecutive occurrences in time or entities in space are independent and exponentially distributed, which is nonsensical in higher dimensions. This paper gives a short proof of the conditioning property for multi-dimensional Poisson point processes.
format Preprint
id arxiv_https___arxiv_org_abs_2508_21303
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Short proof of the conditioning property for multi-dimensional Poisson point processes
Lanchier, Nicolas
Probability
60G55
Poisson processes and one-dimensional Poisson point processes satisfy three main properties: superposition, thinning, and conditioning. The proof of the first two relies on basic estimates involving the Poisson distribution that are also true for multi-dimensional Poisson point processes. In contrast, the proof of conditioning uses that the distances between consecutive occurrences in time or entities in space are independent and exponentially distributed, which is nonsensical in higher dimensions. This paper gives a short proof of the conditioning property for multi-dimensional Poisson point processes.
title Short proof of the conditioning property for multi-dimensional Poisson point processes
topic Probability
60G55
url https://arxiv.org/abs/2508.21303