Physics – Condensed Matter – Statistical Mechanics
Scientific paper
2000-11-09
Pure and Applied Geophysics 160 (12), 2343-2364 (2003)
Physics
Condensed Matter
Statistical Mechanics
pdf document of 21 pages + 2 tables + 20 figures (ps format) + one file giving the regionalization
Scientific paper
10.1007/s00024-003-2397-x
Based on recent results in extreme value theory, we use a new technique for the statistical estimation of distribution tails. Specifically, we use the Gnedenko-Pickands-Balkema-de Haan theorem, which gives a natural limit law for peak-over-threshold values in the form of the Generalized Pareto Distribution (GPD). Useful in finance, insurance, hydrology, we investigate here the earthquake energy distribution described by the Gutenberg-Richter seismic moment-frequency law and analyze shallow earthquakes (depth h < 70 km) in the Harvard catalog over the period 1977-2000 in 18 seismic zones. The whole GPD is found to approximate the tails of the seismic moment distributions quite well above moment-magnitudes larger than mW=5.3 and no statistically significant regional difference is found for subduction and transform seismic zones. We confirm that the b-value is very different in mid-ocean ridges compared to other zones (b=1.50=B10.09 versus b=1.00=B10.05 corresponding to a power law exponent close to 1 versus 2/3) with a very high statistical confidence. We propose a physical mechanism for this, contrasting slow healing ruptures in mid-ocean ridges with fast healing ruptures in other zones. Deviations from the GPD at the very end of the tail are detected in the sample containing earthquakes from all major subduction zones (sample size of 4985 events). We propose a new statistical test of significance of such deviations based on the bootstrap method. The number of events deviating from the tails of GPD in the studied data sets (15-20 at most) is not sufficient for determining the functional form of those deviations. Thus, it is practically impossible to give preference to one of the previously suggested parametric families describing the ends of tails of seismic moment distributions.
Pisarenko V. F.
Sornette Didier
No associations
LandOfFree
Characterization of the frequency of extreme events by the Generalized Pareto Distribution does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Characterization of the frequency of extreme events by the Generalized Pareto Distribution, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Characterization of the frequency of extreme events by the Generalized Pareto Distribution will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-654644