Completely Random Measures

Completely Random Measures is a stochastic process in probability theory that generates random measures on a space such that the measures assigned to disjoint sets are independent, distinguishing it from other random measures by its complete stochastic independence across disjoint measurable sets.

31

Publications

1.8K

Citations

38

Authors

42

Institutions

Publications per year

2017–2026

10

Variants

Completely Random Measure

Authors

38

  1. AL
    Antonio Lijoi

    University of Pavia, Italy

    4 publications · 118 citations

    4

    h-index

  2. FC
    François Caron

    Université de Rouen Normandie, France

    3 publications · 73 citations

    3

    h-index

  3. IP
    Igor Prünster

    University of Pavia, Italy

    3 publications · 94 citations

    3

    h-index

  4. RA
    Raffaele Argiento

    Istituto di Matematica Applicata e Tecnologie Informatiche, Italy

    3 publications · 51 citations

    3

    h-index

  5. MV
    Marina Vannucci

    Rice University, United States

    2 publications · 36 citations

    2

    h-index

1–5 of 38

Venues

  1. 4

    h-index

  2. Advances in Applied Probability

    AAP · 2 publications · 226 citations

    2

    h-index

  3. Bayesian Analysis

    2 publications · 57 citations

    2

    h-index

  4. Electronic Journal of Statistics

    2 publications · 36 citations

    2

    h-index

  5. 2

    h-index

1–5