Conditional Variance Estimation

Conditional Variance Estimation is a statistical method that quantifies the uncertainty of a random variable's realization at unsampled locations given observed data, by computing the variance of the conditional distribution derived from a geostatistical model.

640

Publications

61.3K

Citations

1.1K

Authors

618

Institutions

Publications per year

2017–2026

72

Authors

1.1K

  1. DT
    Dag Tjøstheim

    University of Bergen, Norway

    7 publications · 992 citations

    7

    h-index

  2. RT
    Richard T. Baillie

    Michigan State University, United States

    7 publications · 2.3K citations

    7

    h-index

  3. CB
    Chris Brooks

    University of Reading, United Kingdom

    6 publications · 417 citations

    6

    h-index

  4. SL
    Sébastien Laurent

    UCLouvain, Belgium

    6 publications · 399 citations

    6

    h-index

  5. RF
    Robert F. Engle

    New York University, United States

    6 publications · 9.3K citations

    6

    h-index

1–5 of 1.1K

Venues

  1. Journal of the American Statistical Association

    34 publications · 3.4K citations

    25

    h-index

  2. SSRN Electronic Journal

    Repository · 51 publications · 1.9K citations

    23

    h-index

  3. Journal of Business and Economic Statistics

    JBES · 22 publications · 4.7K citations

    19

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 23 publications · 1.3K citations

    14

    h-index

  5. Journal of Applied Econometrics

    13 publications · 4K citations

    13

    h-index

1–5