Functional Dimension Reduction

Functional Dimension Reduction is a statistical methodology within functional data analysis that reduces the infinite-dimensional functional observations to a finite set of uncorrelated components while preserving the essential structure and variability of the original functional time series.

178

Publications

28.6K

Citations

536

Authors

333

Institutions

Publications per year

2017–2026

61

Authors

536

  1. PK
    Piotr Kokoszka

    Utah State University, United States

    5 publications · 252 citations

    5

    h-index

  2. CM
    Ciprian M. Crainiceanu

    Johns Hopkins University, United States

    5 publications · 274 citations

    5

    h-index

  3. AM
    Ana M. Aguilera

    Universidad de Granada, Spain

    5 publications · 286 citations

    5

    h-index

  4. PV
    Philippe Vieu

    Université Toulouse III - Paul Sabatier, France

    4 publications · 289 citations

    4

    h-index

  5. PH
    Peter Hall

    The University of Melbourne, Australia

    4 publications · 534 citations

    4

    h-index

1–5 of 536

Venues

  1. Journal of the American Statistical Association

    11 publications · 945 citations

    11

    h-index

  2. Journal of Multivariate Analysis

    9 publications · 400 citations

    9

    h-index

  3. arXiv (Cornell University)

    Repository · 6 publications · 245 citations

    6

    h-index

  4. Computational Statistics & Data Analysis

    CSDA · 6 publications · 320 citations

    6

    h-index

  5. Test

    4 publications · 137 citations

    4

    h-index

1–5