Point Process Regression

Point Process Regression is a statistical modeling framework that belongs to the class of point process methods, distinguished by its purpose of estimating the conditional intensity function of event occurrences in continuous space or time as a function of covariates.

26

Publications

1.5K

Citations

93

Authors

58

Institutions

Publications per year

2017–2026

3

Authors

93

  1. RE
    Robert E. Kass

    Carnegie Mellon University, United States

    2 publications · 38 citations

    2

    h-index

  2. HK
    H. Kerem Ciğizoğlu

    Istanbul Technical University, Türkiye

    1 publications · 18 citations

    1

    h-index

  3. AJ
    Anthony J. Swerdlow

    Institute of Cancer Research, United Kingdom

    1 publications · 30 citations

    1

    h-index

  4. MJ
    Michael J. McPhaden

    NOAA Pacific Marine Environmental Laboratory, United States

    1 publications · 22 citations

    1

    h-index

  5. JP
    John P. Donoghue

    Brown University, United States

    1 publications · 42 citations

    1

    h-index

1–5 of 93

Venues

  1. The Annals of Statistics

    2 publications · 309 citations

    2

    h-index

  2. 2

    h-index

  3. Statistica Sinica

    2 publications · 39 citations

    2

    h-index

  4. Neural Computation

    2 publications · 61 citations

    2

    h-index

  5. Journal of Hydrology

    1 publications · 109 citations

    1

    h-index

1–5