ArticlePloS one2024
The nhppp package for simulating non-homogeneous Poisson point processes in R.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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6 citing papers in PubMed.
- A Tutorial on Discrete Event Simulation Models Using a Cost-Effectiveness Analysis Example in R.Medical decision making : an international journal of the Society for Medical Decision Making · 2026Article
- Discrete-Event Simulation Modeling Framework for Cancer Interventions and Population Health in R (DESCIPHR): An Open-Source Pipeline.PharmacoEconomics · 2026Article
- Bladder Cancer Burden in the USA: Population Scenarios for 2040.European urology open science · 2026Article
- A Fast Nonparametric Sampling Method for Time to Event in Individual-Level Simulation Models.Medical decision making : an international journal of the Society for Medical Decision Making · 2025Article
- A Fast Nonparametric Sampling (NPS) Method for Time-to-Event in Individual-Level Simulation Models.medRxiv : the preprint server for health sciences · 2024Article
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2 authors.
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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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