Concepedia

Model-based Population Interpolation

Model-Based Population Interpolation is a population interpolation method that relies on statistical or machine learning models to estimate spatially continuous population distributions from aggregate data by incorporating auxiliary variables and domain-specific assumptions.

3

Publications

116

Citations

9

Authors

5

Institutions

Publications per year

2017–2026

0

Parents

Publications

3

1–3 of 3

Authors

9

  1. DS
    Dezső Schuler

    Semmelweis University, Hungary

    1 publications · 12 citations

    1

    h-index

  2. ST
    Szabolcs Török

    Semmelweis University, Hungary

    1 publications · 12 citations

    1

    h-index

  3. AS
    Andrew S. Mugglin

    University of Minnesota, United States

    1 publications · 87 citations

    1

    h-index

  4. ZJ
    Zsuzsanna Jakab

    Semmelweis University, Hungary

    1 publications · 12 citations

    1

    h-index

  5. KF
    Kosei Fukuda

    Nihon University, Japan

    1 publications · 17 citations

    1

    h-index

1–5 of 9

Institutions

5

  1. Twin Cities Orthopedics

    Edina, United States

    1 h-index

    1 publications

    87 citations

  2. Nihon University

    Tokyo, Japan

    1 h-index

    1 publications

    17 citations

  3. Semmelweis University

    Budapest, Hungary

    1 h-index

    6 publications

    72 citations

  4. Northwestern College - Iowa

    Orange City, United States

    1 h-index

    1 publications

    87 citations

  5. University of Minnesota

    Minneapolis, United States

    1 h-index

    1 publications

    87 citations

1–5 of 5

Venues

  1. 1

    h-index

  2. European Journal of Epidemiology

    1 publications · 12 citations

    1

    h-index

  3. Journal of Population Research

    1 publications · 17 citations

    1

    h-index

1–3