Probability Gain Analysis

Probability Gain Analysis is a methodological framework in seismological forecasting that quantifies the improvement in earthquake prediction accuracy by comparing the conditional probability of seismic events given a precursor to the background probability of such events in its absence, thereby differentiating it from general probabilistic models through its focus on incremental predictive power.

17

Publications

541

Citations

48

Authors

30

Institutions

Publications per year

2017–2026

6

Authors

48

  1. DP
    D. Pantosti

    Istituto Nazionale di Geofisica e Vulcanologia, Italy

    2 publications · 38 citations

    2

    h-index

  2. PH
    Peng Han

    Southern University of Science and Technology, China

    2 publications · 64 citations

    2

    h-index

  3. RC
    Rodolfo Console

    Istituto Nazionale di Geofisica e Vulcanologia, Italy

    2 publications · 38 citations

    2

    h-index

  4. MI
    Masajiro Imoto

    National Research Institute for Earth Science and Disaster Resilience, Japan

    2 publications · 35 citations

    2

    h-index

  5. HC
    Hongyan Chen

    Southern University of Science and Technology, China

    2 publications · 64 citations

    2

    h-index

1–5 of 48

Venues

  1. Bulletin of the Seismological Society of America

    BSSA · 3 publications · 115 citations

    3

    h-index

  2. Entropy

    2 publications · 64 citations

    2

    h-index

  3. Earth Planets and Space

    2 publications · 42 citations

    2

    h-index

  4. Journal of Geophysical Research Atmospheres

    JGR · 2 publications · 34 citations

    2

    h-index

  5. DOAJ (DOAJ: Directory of Open Access Journals)

    Repository · 1 publications · 21 citations

    1

    h-index

1–5