Regular Conditional Probability

Regular Conditional Probability is a probability kernel that assigns to each point in the sample space a probability measure on the measurable space of outcomes, such that it satisfies the condition of being a version of the conditional probability given a sub-σ-algebra and is measurable with respect to the conditioning variable.

25

Publications

825

Citations

34

Authors

19

Institutions

Publications per year

2017–2026

3

Variants

Regular Conditional Distribution

Authors

34

  1. LH
    Louis H. Blake

    College of Staten Island, United States

    2 publications · 53 citations

    2

    h-index

  2. JB
    Joseph B. Kadane

    Carnegie Mellon University, United States

    2 publications · 64 citations

    2

    h-index

  3. MJ
    Mark J. Schervish

    Carnegie Mellon University, United States

    2 publications · 64 citations

    2

    h-index

  4. MJ
    Miloslav Jiřina

    Flinders University, Australia

    2 publications · 47 citations

    2

    h-index

  5. LJ
    LeSheng Jin

    Nanjing Normal University, China

    1 publications · 16 citations

    1

    h-index

1–5 of 34

Venues

  1. The Annals of Probability

    8 publications · 322 citations

    8

    h-index

  2. Pacific Journal of Mathematics

    3 publications · 98 citations

    3

    h-index

  3. Czechoslovak Mathematical Journal

    2 publications · 47 citations

    2

    h-index

  4. Theory of Probability and Its Applications

    1 publications · 10 citations

    1

    h-index

  5. Electronic Journal of Probability

    EJP · 1 publications · 36 citations

    1

    h-index

1–5