Partially Observed Models

Partially Observed Models is a statistical modeling framework within semiparametric modeling that belongs to the class of models incorporating both parametric and nonparametric components, distinguished by its explicit treatment of latent or unobserved variables that influence the observed data but cannot be directly measured.

39

Publications

5.6K

Citations

95

Authors

54

Institutions

Publications per year

2017–2026

9

Variants

Poms

Authors

95

  1. RJ
    Raymond J. Carroll

    Texas A&M University, United States

    3 publications · 196 citations

    3

    h-index

  2. SY
    Serdar Yüksel

    Queen's University, Canada

    2 publications · 72 citations

    2

    h-index

  3. CD
    Charalambos D. Charalambous

    University of Cyprus, Cyprus

    1 publications · 33 citations

    1

    h-index

  4. BK
    Bani K. Mallick

    Texas A&M University, United States

    1 publications · 22 citations

    1

    h-index

  5. ER
    Esther Ruiz

    Universidad Carlos III de Madrid, Spain

    1 publications · 20 citations

    1

    h-index

1–5 of 95

Venues

  1. IFAC Proceedings Volumes

    2 publications · 22 citations

    2

    h-index

  2. Journal of Multivariate Analysis

    2 publications · 41 citations

    2

    h-index

  3. Operations Research

    2 publications · 67 citations

    2

    h-index

  4. 2

    h-index

  5. RePEc: Research Papers in Economics

    Repository · 2 publications · 70 citations

    2

    h-index

1–5