The Ease of Fitting but Futility of Testing a Nonstationary Poisson Processes from One Sample Path

Barry L. Nelson, Lawrence M. Leemis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

The nonstationary Poisson process (NSPP) is a workhorse tool for modeling and simulating arrival processes with time-dependent rates. In many applications only a single sequence of arrival times are observed. While one sample path is sufficient for estimating the arrival rate or integrated rate function of the process - as we illustrate in this paper - we show that testing for Poissonness, in the general case, is futile. In other words, when only a single sequence of arrival data are observed then one can fit an NSPP to it, but the choice of NSPP can only be justified by an understanding of the underlying process physics, or a leap of faith, not by testing the data. This result suggests the need for sensitivity analysis when such a model is used to generate arrivals in a simulation.

Original languageEnglish (US)
Title of host publicationProceedings of the 2020 Winter Simulation Conference, WSC 2020
EditorsK.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages266-276
Number of pages11
ISBN (Electronic)9781728194998
DOIs
StatePublished - Dec 14 2020
Event2020 Winter Simulation Conference, WSC 2020 - Orlando, United States
Duration: Dec 14 2020Dec 18 2020

Publication series

NameProceedings - Winter Simulation Conference
Volume2020-December
ISSN (Print)0891-7736

Conference

Conference2020 Winter Simulation Conference, WSC 2020
Country/TerritoryUnited States
CityOrlando
Period12/14/2012/18/20

ASJC Scopus subject areas

  • Software
  • Modeling and Simulation
  • Computer Science Applications

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