Multivariate Characteristic Functions

Multivariate Characteristic Functions is a mathematical construct in probability theory that extends the concept of characteristic functions to multivariate random vectors by uniquely representing the joint probability distribution through the expected value of the complex exponential function of a linear combination of the vector components.

378

Publications

20.5K

Citations

549

Authors

356

Institutions

Publications per year

2017–2026

25

Variants

Multivariate Characteristic Function

Authors

549

  1. AK
    Arjun K. Gupta

    Bowling Green State University, United States

    6 publications · 136 citations

    6

    h-index

  2. MG
    Marc G. Genton

    King Abdullah University of Science and Technology, Saudi Arabia

    4 publications · 182 citations

    4

    h-index

  3. SN
    Saralees Nadarajah

    University of Manchester, United Kingdom

    4 publications · 174 citations

    4

    h-index

  4. DK
    Debasis Kundu

    Indian Institute of Technology Kanpur, India

    4 publications · 117 citations

    4

    h-index

  5. AG
    Alan Genz

    Washington State University, United States

    3 publications · 1.5K citations

    3

    h-index

1–5 of 549

Venues

  1. Journal of Multivariate Analysis

    40 publications · 2.2K citations

    23

    h-index

  2. The Annals of Mathematical Statistics

    18 publications · 2.1K citations

    17

    h-index

  3. Statistics & Probability Letters

    14 publications · 324 citations

    12

    h-index

  4. Journal of the American Statistical Association

    12 publications · 2.7K citations

    11

    h-index

  5. 9

    h-index

1–5