Gaussian Random Field Simulation

Gaussian Random Field Simulation is a conditional simulation method that generates realizations of a spatially correlated random field under the assumption that the underlying distribution is multivariate Gaussian, distinguished by its reliance on Gaussian process theory to model uncertainty and spatial dependence.

143

Publications

10.1K

Citations

304

Authors

200

Institutions

Publications per year

2017–2026

27

Authors

304

  1. XE
    Xavier Emery

    University of Chile, Chile

    10 publications · 563 citations

    10

    h-index

  2. EP
    Emilio Porcu

    Federico Santa María Technical University, Chile

    4 publications · 125 citations

    4

    h-index

  3. IF
    Isaac Freund

    Bar-Ilan University, Israel

    4 publications · 424 citations

    4

    h-index

  4. AC
    Alejandro C. Frery

    Universidade Federal de Alagoas, Brazil

    3 publications · 58 citations

    3

    h-index

  5. GD
    George Deodatis

    Columbia University, United States

    3 publications · 550 citations

    3

    h-index

1–5 of 304

Venues

  1. The Astrophysical Journal

    ApJ · 12 publications · 918 citations

    12

    h-index

  2. Journal of Engineering Mechanics

    8 publications · 895 citations

    8

    h-index

  3. 6

    h-index

  4. Computers & Geosciences

    CAGEO · 6 publications · 366 citations

    6

    h-index

  5. Water Resources Research

    4 publications · 509 citations

    4

    h-index

1–5