Spatial Measurement Error Models

Spatial Measurement Error Models is a class of Bayesian hierarchical models that account for geographic dependence and uncertainty in observed measurements by explicitly incorporating spatial correlation structures into the measurement error process.

69

Publications

3.1K

Citations

213

Authors

131

Institutions

Publications per year

2017–2026

16

Authors

213

  1. YL
    Yee Leung

    Chinese University of Hong Kong, Hong Kong SAR China

    3 publications · 126 citations

    3

    h-index

  2. YM
    Yiorgos Makris

    The University of Texas at Dallas, United States

    2 publications · 32 citations

    2

    h-index

  3. MF
    Michael F. Goodchild

    University of California, Santa Barbara, United States

    2 publications · 45 citations

    2

    h-index

  4. NK
    Nathan Kupp

    Yale University, United States

    2 publications · 32 citations

    2

    h-index

  5. JM
    John M. Carulli

    Texas Instruments (United States), United States

    2 publications · 32 citations

    2

    h-index

1–5 of 213

Venues

  1. Journal of Geographical Systems

    3 publications · 70 citations

    3

    h-index

  2. Environmetrics

    3 publications · 79 citations

    3

    h-index

  3. 2

    h-index

  4. Regional Science and Urban Economics

    2 publications · 54 citations

    2

    h-index

  5. Biostatistics

    2 publications · 270 citations

    2

    h-index

1–5