nhppp: Simulating Nonhomogeneous Poisson Point Processes in R

2024/02/01 by Thomas A Trikalinos, Trikalinos, Thomas A., Yuliia Sereda +1
Decision Sciences · #Computation (stat.CO) #FOS: Computer and information sciences #Methodology (stat.ME) #demographic modeling and climate adaptation

paper · pdf · doi:10.48550/arxiv.2402.00358

openalex publication_date 2024/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We introduce the `nhppp' package for simulating events from one-dimensional non-homogeneous Poisson point processes (NHPPPs) in R fast and with a small memory footprint. We developed it to facilitate the sampling of event times in discrete event and statistical simulations. The package's functions are based on three algorithms that provably sample from a target NHPPP: the time-transformation of a homogeneous Poisson process (of intensity one) via the inverse of the integrated intensity function; the generation of a Poisson number of order statistics from a fixed density function; and the thinning of a majorizing NHPPP via an acceptance-rejection scheme. We present a study of numerical accuracy and time performance of the algorithms. We illustrate use with simple reproducible examples.

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