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Hypothesis testing and earthquake prediction.

D D Jackson1

  • 1Southern California Earthquake Center, University of California, Los Angeles, CA 90095-1567, USA.

Proceedings of the National Academy of Sciences of the United States of America
|April 30, 1996
PubMed
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Formulating testable earthquake prediction hypotheses in advance is crucial for validation. Rigorous testing requires specifying conditional rate density or probabilities, and comparing predictions against a null hypothesis for reliable assessment.

Area of Science:

  • Geophysics
  • Seismology
  • Earthquake Science

Background:

  • Earthquake prediction requires rigorous validation of proposed methods.
  • Assessing prediction accuracy necessitates clearly defined hypotheses and testing protocols.
  • Understanding 'normal' seismic behavior is essential for identifying increased earthquake probability periods.

Purpose of the Study:

  • To outline requirements for testing earthquake prediction hypotheses.
  • To emphasize the importance of advance hypothesis formulation for method validation.
  • To propose methods for testing earthquake predictions against observed seismic activity.

Main Methods:

  • Specifying conditional rate density (probability per unit time, area, and magnitude).
  • Defining probabilities for specified intervals of time, space, and magnitude.

Related Experiment Videos

  • Testing hypotheses by comparing actual earthquakes to predictions using statistical methods (e.g., likelihood scores, likelihood ratios).

    • Main Results:

    • Three primary testing approaches are identified: comparing counts, comparing likelihood scores, and comparing likelihood ratios against a null hypothesis.
    • Self-consistency tests (comparing counts or likelihood scores) are distinguished from direct hypothesis comparison (likelihood ratio).
    • Predictions lacking probabilistic statements are difficult to test rigorously.

    Conclusions:

    • Advance formulation of testable earthquake prediction hypotheses is vital due to long validation times.
    • Robust testing requires probabilistic statements and comparison with a null hypothesis representing normal seismic behavior.
    • The proposed testing framework enables objective evaluation of earthquake prediction models.