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A Spline-based Method for Modelling and Generating a Nonhomogeneous Poisson Process

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A Spline-based Method for Modelling and Generating a Nonhomogeneous Poisson Process. / Morgan, Lucy; Nelson, Barry; Titman, Andrew et al.
Proceedings of the 2019 Winter Simulation Conference. IEEE Press, 2020.

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

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Morgan L, Nelson B, Titman A, Worthington D. A Spline-based Method for Modelling and Generating a Nonhomogeneous Poisson Process. In Proceedings of the 2019 Winter Simulation Conference. IEEE Press. 2020 doi: 10.1109/WSC40007.2019.9004867

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@inproceedings{abbc80b8c0cd4545834647712c137e93,
title = "A Spline-based Method for Modelling and Generating a Nonhomogeneous Poisson Process",
abstract = "This paper presents a spline-based input modelling method for inferring the intensity function of a nonhomogeneous Poisson process (NHPP) given arrival-time observations. A simple method for generating arrivals from the resulting intensity function is also presented. Splines are a natural choice for modelling intensity functions as they are smooth by construction, and highly flexible. Although flexibility is an advantage in terms of reducing the bias with respect to the true intensity function, it can lead to overfitting. Our method is therefore based on maximising the penalised NHPP log-likelihood, where the penalty is a measure of rapid changes in the spline-based representation. An empirical comparison of the spline-based method against two recently developed input modelling techniques is presented, along with an illustration of the method given arrivals from a real-world accident and emergency (A&E) department. ",
author = "Lucy Morgan and Barry Nelson and Andrew Titman and David Worthington",
note = "{\textcopyright}2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. ",
year = "2020",
month = feb,
day = "20",
doi = "10.1109/WSC40007.2019.9004867",
language = "English",
isbn = "9781728120522",
booktitle = "Proceedings of the 2019 Winter Simulation Conference",
publisher = "IEEE Press",

}

RIS

TY - GEN

T1 - A Spline-based Method for Modelling and Generating a Nonhomogeneous Poisson Process

AU - Morgan, Lucy

AU - Nelson, Barry

AU - Titman, Andrew

AU - Worthington, David

N1 - ©2020 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

PY - 2020/2/20

Y1 - 2020/2/20

N2 - This paper presents a spline-based input modelling method for inferring the intensity function of a nonhomogeneous Poisson process (NHPP) given arrival-time observations. A simple method for generating arrivals from the resulting intensity function is also presented. Splines are a natural choice for modelling intensity functions as they are smooth by construction, and highly flexible. Although flexibility is an advantage in terms of reducing the bias with respect to the true intensity function, it can lead to overfitting. Our method is therefore based on maximising the penalised NHPP log-likelihood, where the penalty is a measure of rapid changes in the spline-based representation. An empirical comparison of the spline-based method against two recently developed input modelling techniques is presented, along with an illustration of the method given arrivals from a real-world accident and emergency (A&E) department.

AB - This paper presents a spline-based input modelling method for inferring the intensity function of a nonhomogeneous Poisson process (NHPP) given arrival-time observations. A simple method for generating arrivals from the resulting intensity function is also presented. Splines are a natural choice for modelling intensity functions as they are smooth by construction, and highly flexible. Although flexibility is an advantage in terms of reducing the bias with respect to the true intensity function, it can lead to overfitting. Our method is therefore based on maximising the penalised NHPP log-likelihood, where the penalty is a measure of rapid changes in the spline-based representation. An empirical comparison of the spline-based method against two recently developed input modelling techniques is presented, along with an illustration of the method given arrivals from a real-world accident and emergency (A&E) department.

U2 - 10.1109/WSC40007.2019.9004867

DO - 10.1109/WSC40007.2019.9004867

M3 - Conference contribution/Paper

SN - 9781728120522

BT - Proceedings of the 2019 Winter Simulation Conference

PB - IEEE Press

ER -