Time Series Modeling

Time Series Modeling is a statistical modeling technique that characterizes and analyzes sequentially ordered, time-dependent observations to capture temporal dependencies and forecast future values based on past and present data.

19.4K

Publications

1.6M

Citations

38.8K

Authors

6.9K

Institutions

Publications per year

2017–2026

7.5K

Authors

38.8K

  1. AH
    Andrew Harvey

    University of Cambridge, United Kingdom

    62 publications · 12.7K citations

    40

    h-index

  2. RS
    Ruey S. Tsay

    University of Chicago, United States

    50 publications · 6.7K citations

    35

    h-index

  3. SJ
    Siem Jan Koopman

    Vrije Universiteit Amsterdam, Netherlands

    57 publications · 6.6K citations

    35

    h-index

  4. EE
    Erol Eğrioğlu

    Giresun University, Türkiye

    55 publications · 3K citations

    32

    h-index

  5. CW
    Clive W. J. Granger

    University of California San Diego, United States

    44 publications · 13.3K citations

    31

    h-index

1–5 of 38.8K

Venues

  1. Journal of the American Statistical Association

    393 publications · 98.8K citations

    116

    h-index

  2. Expert Systems with Applications

    256 publications · 24.3K citations

    83

    h-index

  3. International Journal of Forecasting

    273 publications · 31.7K citations

    81

    h-index

  4. Journal of Time Series Analysis

    334 publications · 31.6K citations

    73

    h-index

  5. Neurocomputing

    180 publications · 22.2K citations

    72

    h-index

1–5