Likelihood Inference

Likelihood Inference is a statistical method that belongs to the class of inference techniques in spatial point process analysis, distinguished by its use of the likelihood function to estimate model parameters and assess uncertainty based on the observed spatial point pattern.

749

Publications

99.6K

Citations

1.5K

Authors

725

Institutions

Publications per year

2017–2026

148

Authors

1.5K

  1. NB
    N. Balakrishnan

    McMaster University, Canada

    22 publications · 1.4K citations

    20

    h-index

  2. YZ
    Yichuan Zhao

    Georgia State University, United States

    8 publications · 186 citations

    8

    h-index

  3. SP
    Suvra Pal

    The University of Texas at Arlington, United States

    8 publications · 258 citations

    8

    h-index

  4. BD
    B. D. Wandelt

    Institut d'Astrophysique de Paris, France

    8 publications · 606 citations

    8

    h-index

  5. CV
    Cristiano Varin

    Ca' Foscari University of Venice, Italy

    7 publications · 1.5K citations

    7

    h-index

1–5 of 1.5K

Venues

  1. Biometrika

    31 publications · 2.5K citations

    23

    h-index

  2. 22

    h-index

  3. Journal of the American Statistical Association

    30 publications · 3.5K citations

    22

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 24 publications · 844 citations

    18

    h-index

  5. Biometrics

    19 publications · 913 citations

    17

    h-index

1–5