@inproceedings{af910d0bde7f40658effd8ce9e07d52b,
title = "The Ease of Fitting but Futility of Testing a Nonstationary Poisson Processes from One Sample Path",
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.",
author = "Nelson, {Barry L.} and Leemis, {Lawrence M.}",
note = "Funding Information: Nelson{\textquoteright}s work is partially supported by National Science Foundation Grant Number DMS-1854562. The authors thank Shane Henderson for comments on an early draft. Publisher Copyright: {\textcopyright} 2020 IEEE.; 2020 Winter Simulation Conference, WSC 2020 ; Conference date: 14-12-2020 Through 18-12-2020",
year = "2020",
month = dec,
day = "14",
doi = "10.1109/WSC48552.2020.9383930",
language = "English (US)",
series = "Proceedings - Winter Simulation Conference",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "266--276",
editor = "K.-H. Bae and B. Feng and S. Kim and S. Lazarova-Molnar and Z. Zheng and T. Roeder and R. Thiesing",
booktitle = "Proceedings of the 2020 Winter Simulation Conference, WSC 2020",
address = "United States",
}