Continuous Joint Distributions

Continuous Joint Distributions is a type of joint probability distribution that describes the likelihood of two or more continuous random variables simultaneously taking on specific values within a continuous domain, characterized by a probability density function that integrates to one over the entire space.

116

Publications

7.3K

Citations

233

Authors

145

Institutions

Publications per year

2017–2026

12

Authors

233

  1. SA
    Sigeo Aki

    The University of Osaka, Japan

    5 publications · 115 citations

    5

    h-index

  2. DC
    Douglas C. Montgomery

    Arizona State University, United States

    3 publications · 723 citations

    3

    h-index

  3. KI
    Kiyoshi Inoue

    Osaka Prefectural Institute of Public Health, Japan

    3 publications · 38 citations

    3

    h-index

  4. WW
    William W. Hines

    Georgia Institute of Technology, United States

    3 publications · 723 citations

    3

    h-index

  5. DE
    Doug Emery

    Walters Art Museum, United States

    2 publications · 69 citations

    2

    h-index

1–5 of 233

Venues

  1. 6

    h-index

  2. The Annals of Mathematical Statistics

    5 publications · 1.1K citations

    5

    h-index

  3. 4

    h-index

  4. Technometrics

    4 publications · 543 citations

    4

    h-index

  5. Journal of Applied Probability

    JAP · 4 publications · 334 citations

    4

    h-index

1–5