Data Detrending

Data Detrending is a preprocessing technique in hydrologic time series analysis that belongs to the class of data normalization methods, specifically distinguished by its purpose of removing systematic non-stationary components, such as long-term trends, to facilitate the analysis of underlying stochastic processes.

214

Publications

25.3K

Citations

808

Authors

462

Institutions

Publications per year

2017–2026

57

Authors

808

  1. HE
    H. Eugene Stanley

    Boston University, United States

    8 publications · 6.6K citations

    8

    h-index

  2. KK
    Ken Kiyono

    The University of Osaka, Japan

    6 publications · 206 citations

    6

    h-index

  3. PS
    Pengjian Shang

    Beijing Jiaotong University, China

    5 publications · 160 citations

    5

    h-index

  4. WZ
    Wei‐Xing Zhou

    East China University of Science and Technology, China

    5 publications · 1.2K citations

    5

    h-index

  5. BP
    Boris Podobnik

    University of Rijeka, Croatia

    5 publications · 2.9K citations

    5

    h-index

1–5 of 808

Venues

  1. 20

    h-index

  2. Physical Review E

    PRE · 7 publications · 1.3K citations

    7

    h-index

  3. Astronomy and Astrophysics

    4 publications · 130 citations

    4

    h-index

  4. SSRN Electronic Journal

    Repository · 4 publications · 75 citations

    4

    h-index

  5. Nonlinear Dynamics

    3 publications · 76 citations

    3

    h-index

1–5