Covariance Function Estimation

Covariance Function Estimation is a statistical modeling procedure that identifies the mathematical function characterizing the spatial dependence structure among observations by estimating how covariance varies as a function of distance and direction in a given domain.

284

Publications

22.5K

Citations

551

Authors

336

Institutions

Publications per year

2017–2026

45

Authors

551

  1. ML
    Michael L. Stein

    University of Chicago, United States

    7 publications · 407 citations

    7

    h-index

  2. EP
    Emilio Porcu

    Federico Santa María Technical University, Chile

    6 publications · 447 citations

    6

    h-index

  3. PK
    Peter K. Kitanidis

    Stanford University, United States

    5 publications · 816 citations

    5

    h-index

  4. MB
    Moreno Bevilacqua

    University of Valparaíso, Chile

    4 publications · 365 citations

    4

    h-index

  5. DY
    D. Y. Lin

    University of North Carolina at Chapel Hill, United States

    4 publications · 873 citations

    4

    h-index

1–5 of 551

Venues

  1. Journal of the American Statistical Association

    13 publications · 1.3K citations

    13

    h-index

  2. The Annals of Statistics

    11 publications · 1.2K citations

    11

    h-index

  3. Water Resources Research

    10 publications · 1.2K citations

    10

    h-index

  4. arXiv (Cornell University)

    Repository · 9 publications · 830 citations

    9

    h-index

  5. Biometrika

    8 publications · 666 citations

    8

    h-index

1–5