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Title: THE EASE OF FITTING BUT FUTILITY OF TESTING A NONSTATIONARY POISSON PROCESSES FROM ONE SAMPLE PATH
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.
Authors:
;
Editors:
Bae, K-H; Feng, B; Kim, S; Lazarova-Molnar, S; Zheng, Z; Roeder, T; Thiesing, R
Award ID(s):
1854562
Publication Date:
NSF-PAR ID:
10233327
Journal Name:
Proceedings of the Winter Simulation Conference
Page Range or eLocation-ID:
266-276
ISSN:
1558-4305
Sponsoring Org:
National Science Foundation
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