Nonlinear Time-series Analysis

Nonlinear Time-Series Analysis is a methodological framework within time-series analysis that specifically addresses the modeling, detection, and prediction of dynamic processes governed by nonlinear deterministic or stochastic mechanisms, distinguishing it from linear approaches by its capacity to capture regime shifts, feedback loops, and complex dependencies inherent in nonlinear systems.

1.4K

Publications

113.4K

Citations

3.1K

Authors

1.3K

Institutions

Publications per year

2017–2026

276

Authors

3.1K

  1. JK
    Jürgen Kurths

    Potsdam Institute for Climate Impact Research, Germany

    13 publications · 1.6K citations

    13

    h-index

  2. TS
    Thomas Schreiber

    University of Wuppertal, Germany

    13 publications · 4.4K citations

    13

    h-index

  3. RS
    Ruey S. Tsay

    University of Chicago, United States

    13 publications · 2.5K citations

    12

    h-index

  4. MS
    Michael Small

    The University of Western Australia, Australia

    12 publications · 845 citations

    11

    h-index

  5. NM
    Norbert Marwan

    Potsdam Institute for Climate Impact Research, Germany

    11 publications · 2.1K citations

    11

    h-index

1–5 of 3.1K

Venues

  1. 32

    h-index

  2. Journal of the American Statistical Association

    29 publications · 4.4K citations

    27

    h-index

  3. Physical Review E

    PRE · 29 publications · 2.4K citations

    20

    h-index

  4. 19

    h-index

  5. International Journal of Bifurcation and Chaos

    IJBC · 30 publications · 2K citations

    19

    h-index

1–5