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 language | English (US) |
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Title of host publication | Proceedings of the 2020 Winter Simulation Conference, WSC 2020 |
Editors | K.-H. Bae, B. Feng, S. Kim, S. Lazarova-Molnar, Z. Zheng, T. Roeder, R. Thiesing |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 266-276 |
Number of pages | 11 |
ISBN (Electronic) | 9781728194998 |
DOIs | |
State | Published - Dec 14 2020 |
Event | 2020 Winter Simulation Conference, WSC 2020 - Orlando, United States Duration: Dec 14 2020 → Dec 18 2020 |
Publication series
Name | Proceedings - Winter Simulation Conference |
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Volume | 2020-December |
ISSN (Print) | 0891-7736 |
Conference
Conference | 2020 Winter Simulation Conference, WSC 2020 |
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Country/Territory | United States |
City | Orlando |
Period | 12/14/20 → 12/18/20 |
Funding
Nelson’s work is partially supported by National Science Foundation Grant Number DMS-1854562. The authors thank Shane Henderson for comments on an early draft.
ASJC Scopus subject areas
- Software
- Modeling and Simulation
- Computer Science Applications