Poisson Process Estimation

Poisson Process Estimation is a statistical methodology that belongs to the class of point process inference techniques, distinguished by its focus on estimating the intensity function or rate parameter of a Poisson process from observed event data.

403

Publications

23.6K

Citations

777

Authors

461

Institutions

Publications per year

2017–2026

41

Authors

777

  1. JR
    James R. Wilson

    North Carolina State University, United States

    7 publications · 179 citations

    7

    h-index

  2. ME
    Michael E. Kuhl

    Rochester Institute of Technology, United States

    7 publications · 178 citations

    7

    h-index

  3. IW
    I Wayan Mangku

    IPB University, Indonesia

    6 publications · 118 citations

    6

    h-index

  4. RH
    Roelof Helmers

    Centrum Wiskunde & Informatica, Netherlands

    5 publications · 115 citations

    5

    h-index

  5. RZ
    Ričardas Zitikis

    Western University, Canada

    5 publications · 116 citations

    5

    h-index

1–5 of 777

Venues

  1. Journal of the American Statistical Association

    16 publications · 1.1K citations

    15

    h-index

  2. Biometrika

    17 publications · 1.1K citations

    14

    h-index

  3. The Annals of Statistics

    14 publications · 698 citations

    13

    h-index

  4. Biometrics

    13 publications · 400 citations

    12

    h-index

  5. Journal of Statistical Computation and Simulation

    JSCS · 10 publications · 257 citations

    10

    h-index

1–5