Poisson Process Simulation

Poisson Process Simulation is a computational method that generates realizations of a Poisson process by modeling the random occurrence of events in continuous time or space according to a specified intensity function, distinguishing it from other stochastic simulation techniques through its reliance on exponential inter-arrival times and the superposition of independent increments.

170

Publications

10.4K

Citations

417

Authors

275

Institutions

Publications per year

2017–2026

25

Authors

417

  1. JR
    James R. Wilson

    North Carolina State University, United States

    4 publications · 198 citations

    4

    h-index

  2. PL
    Peter Lewis

    Naval Postgraduate School, United States

    4 publications · 994 citations

    4

    h-index

  3. GS
    Gerald S. Shedler

    IBM (United States), United States

    4 publications · 994 citations

    4

    h-index

  4. ME
    Michael E. Kuhl

    Rochester Institute of Technology, United States

    3 publications · 71 citations

    3

    h-index

  5. PS
    Paul S.P. Cowpertwait

    Massey University, New Zealand

    3 publications · 199 citations

    3

    h-index

1–5 of 417

Venues

  1. The Journal of Chemical Physics

    4 publications · 1.3K citations

    4

    h-index

  2. Journal of Applied Probability

    JAP · 4 publications · 129 citations

    4

    h-index

  3. Water Resources Research

    3 publications · 152 citations

    3

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 78 citations

    3

    h-index

  5. SIMULATION

    3 publications · 64 citations

    3

    h-index

1–5