Functional Time Series Analysis

Functional Time Series Analysis is a subfield of time series analysis that develops statistical methods for modeling, inference, and forecasting when each time-indexed observation is a function defined on a continuum (such as a curve or surface) rather than a finite-dimensional vector.

449

Publications

31.2K

Citations

1.1K

Authors

547

Institutions

Publications per year

2017–2026

171

Authors

1.1K

  1. PK
    Piotr Kokoszka

    Utah State University, United States

    18 publications · 1.3K citations

    16

    h-index

  2. HL
    Han Lin Shang

    Australian National University, Australia

    18 publications · 824 citations

    14

    h-index

  3. GR
    Gregory Rice

    University of Waterloo, Canada

    11 publications · 529 citations

    11

    h-index

  4. SH
    Siegfried Hörmann

    Graz University of Technology, Austria

    9 publications · 1.1K citations

    9

    h-index

  5. LH
    Lajos Horváth

    University of Utah, United States

    9 publications · 737 citations

    9

    h-index

1–5 of 1.1K

Venues

  1. NeuroImage

    27 publications · 5.6K citations

    23

    h-index

  2. Journal of Time Series Analysis

    14 publications · 409 citations

    13

    h-index

  3. Journal of the American Statistical Association

    13 publications · 856 citations

    13

    h-index

  4. Human Brain Mapping

    13 publications · 1.9K citations

    12

    h-index

  5. IEEE Transactions on Medical Imaging

    11 publications · 3.6K citations

    11

    h-index

1–5