Mixed Poisson Processes

Mixed Poisson Processes is a type of counting process in which the intensity measure is itself a random variable, extending the standard Poisson process by allowing for heterogeneity in the arrival rate through a mixing distribution.

128

Publications

6.7K

Citations

257

Authors

166

Institutions

Publications per year

2017–2026

19

Variants

Doubly Stochastic Poisson Processes

Authors

257

  1. GE
    Gordon E. Willmot

    University of Waterloo, Canada

    8 publications · 379 citations

    8

    h-index

  2. RJ
    Richard J. Cook

    University of Waterloo, Canada

    5 publications · 115 citations

    5

    h-index

  3. OH
    Ole Hesselager

    University of Copenhagen, Denmark

    4 publications · 140 citations

    4

    h-index

  4. DL
    Demetrios L. Antzoulakos

    University of Piraeus, Greece

    2 publications · 26 citations

    2

    h-index

  5. BC
    B. C. Brookes

    University College London, United Kingdom

    2 publications · 149 citations

    2

    h-index

1–5 of 257

Venues

  1. Astin Bulletin

    10 publications · 375 citations

    10

    h-index

  2. Scandinavian Actuarial Journal

    11 publications · 403 citations

    10

    h-index

  3. Journal of Applied Probability

    JAP · 8 publications · 269 citations

    8

    h-index

  4. Insurance Mathematics and Economics

    4 publications · 102 citations

    4

    h-index

  5. The Annals of Statistics

    3 publications · 96 citations

    3

    h-index

1–5