Functional Spatio-temporal Data Analysis

Functional Spatio-Temporal Data Analysis is a statistical methodology that extends functional data analysis to spatially indexed time series by modeling data as functions varying smoothly over both space and time, thereby enabling the extraction of latent spatio-temporal patterns through functional basis representations.

112

Publications

5.2K

Citations

404

Authors

243

Institutions

Publications per year

2017–2026

44

Authors

404

  1. PK
    Piotr Kokoszka

    Utah State University, United States

    5 publications · 130 citations

    5

    h-index

  2. JT
    J. Taboada

    Universidade de Vigo, Spain

    3 publications · 113 citations

    3

    h-index

  3. MR
    Matthew Reimherr

    Pennsylvania State University, United States

    3 publications · 88 citations

    3

    h-index

  4. JM
    Javier Martínez Martínez

    Universidade de Vigo, Spain

    2 publications · 71 citations

    2

    h-index

  5. DL
    Diane Lambert

    AT&T (United States), United States

    2 publications · 63 citations

    2

    h-index

1–5 of 404

Venues

  1. NeuroImage

    6 publications · 866 citations

    6

    h-index

  2. Scientific Reports

    4 publications · 133 citations

    4

    h-index

  3. Environmetrics

    4 publications · 136 citations

    4

    h-index

  4. arXiv (Cornell University)

    Repository · 3 publications · 76 citations

    3

    h-index

  5. Journal of Computational and Graphical Statistics

    JCGS · 3 publications · 480 citations

    3

    h-index

1–5