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Nonparametric Estimation of the Cumulative Intensity Function for a Nonhomogeneous Poisson Process from Overlapping Realizations

Author

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  • Bradford L. Arkin

    (Reliable Software Technologies, Sterling, Virginia 20166)

  • Lawrence M. Leemis

    (Department of Mathematics, The College of William ... Mary, Williamsburg, Virginia 23187)

Abstract

A nonparametric technique for estimating the cumulative intensity function of a nonhomogeneous Poisson process from one or more realizations on an interval is extended here to include realizations that overlap. This technique does not require any arbitrary parameters from the modeler, and the estimated cumulative intensity function can be used to generate a point process for simulation by inversion.

Suggested Citation

  • Bradford L. Arkin & Lawrence M. Leemis, 2000. "Nonparametric Estimation of the Cumulative Intensity Function for a Nonhomogeneous Poisson Process from Overlapping Realizations," Management Science, INFORMS, vol. 46(7), pages 989-998, July.
    • Handle: RePEc:inm:ormnsc:v:46:y:2000:i:7:p:989-998
    DOI: 10.1287/mnsc.46.7.989.12037
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    References listed on IDEAS

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    1. Lawrence M. Leemis, 1991. "Nonparametric Estimation of the Cumulative Intensity Function for a Nonhomogeneous Poisson Process," Management Science, INFORMS, vol. 37(7), pages 886-900, July.
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    Cited by:

    1. Armann Ingolfsson & Elvira Akhmetshina & Susan Budge & Yongyue Li & Xudong Wu, 2007. "A Survey and Experimental Comparison of Service-Level-Approximation Methods for Nonstationary M(t)/M/s(t) Queueing Systems with Exhaustive Discipline," INFORMS Journal on Computing, INFORMS, vol. 19(2), pages 201-214, May.
    2. Michael E. Kuhl & Sachin G. Sumant & James R. Wilson, 2006. "An Automated Multiresolution Procedure for Modeling Complex Arrival Processes," INFORMS Journal on Computing, INFORMS, vol. 18(1), pages 3-18, February.

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