The Area Skill Score Statistic for Evaluating Earthquake Predictability Experiments

Pure and Applied Geophysics

Volumn 167, Issue 8-9, 2010, Pages 893-906

  Zechar, J Douglas ^a,b   Jordan, Thomas H ^a  

^a UNIVERSITY OF SOUTHERN CALIFORNIA   (United States)

^b International Research Institute for Climate and Society   (United States)

Author keywords

Earthquake predictability; Earthquake prediction; Error diagram; Molchan diagram; Statistical seismology

Indexed keywords

CONTINUOUS OBSERVATION; DISCRETIZATIONS; EARTHQUAKE PREDICTION; EFFICIENT ALGORITHM; EXACT ANALYTICAL SOLUTIONS; EXACT DISTRIBUTION; GAUSSIAN APPROXIMATIONS; MOLCHAN DIAGRAM; PERFORMANCE METRICES; SIMULATION PROCEDURES; SKILL SCORE; STATISTICAL CHARACTERIZATION; STATISTICAL PROPERTIES; STATISTICAL SEISMOLOGY;

ALGORITHMS; EARTHQUAKES; EXPERIMENTS; STATISTICS;

FORECASTING;

DIAGRAM; EARTHQUAKE PREDICTION; GAUSSIAN METHOD; NUMERICAL MODEL; SEISMOLOGY; STATISTICAL ANALYSIS;

EID: 77952592006     PISSN: 00334553     EISSN: 14209136     Source Type: Journal    
DOI: 10.1007/s00024-010-0086-0     Document Type: Article

References (13)

1. Abramowitz, M. and Stegun, I. A., Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables (Dover, New York 1972).
2. Field, E. H. (2007), Overview of the working group for the development of Regional Earthquake Likelihood Models (RELM), Seismol. Res. Lett. 78(1), 7-16.
3. Keilis-Borok, V. I., Shebalin, P. N., Gabrielov, A. and Turcotte, D. L. (2004), Reverse tracing of short-term earthquake precursors, Phys. Earth Planet. Inter. 145, 75-85.
4. wHRV≥5. 8", Tectonophys. 413, 25-31.
5. Mason, I. B., Binary events, In Forecast Verification (eds. Jolliffe, I. T. and Stephenson, D. B.) (Wiley, Hoboken 2003) pp. 37-76.
6. Molchan, G. M. (1990), Strategies in strong earthquake prediction, Phys. Earth and Planet. Inter. 61, 84-98.
7. Molchan, G. M. (1991), Structure of optimal strategies in earthquake prediction, Tectonophys. 193, 267-276.
8. Molchan, G. M. and Kagan, Y. Y. (1992), Earthquake prediction and its optimization, J. Geophys. Res. 97, 4823-4838.
9. Rundle, J. B., Tiampo, K., Klein, W. and Sa Martins, J. S. (2002), Self-organization in leaky threshold systems: The influence of near-mean field dynamics and its implications for earthquakes, neurobiology, and forecasting, Proc. Natl. Acad. Sci. USA. 99, 2514-2521.
10. Sadooghi-Alvandi, S. M., Nematollahi, A. R. and Habibi, R. (2007), On the distribution of the sum of independent uniform random variables, Stat. Papers doi: 10. 1007/s00362-007-0049-4.
11. Schorlemmer, D., Zechar, J. D., Werner, M. J., Field, E. H., Jackson, D. D. and Jordan, T. H. (2010), First results of the Regional Earthquake Likelihood Models experiment, Pure Appl. Geophys. doi: 10. 1007/s00024-010-0081-5.
12. Shebalin, P. N., Keilis-Borok, V. I., Gabrielov, A., Zaliapin, I. and Turcotte, D. (2006), Short-term earthquake prediction by reverse analysis of lithosphere dynamics, Tectonophys, 413, 63-75.
13. Zechar, J. D. and Jordan, T. H. (2008), Testing alarm-based earthquake predictions, Geophys. J. Inter. 172(2), 715-724. doi: 10. 1111/j. 1365-246X. 2007. 03676. x.