www.nonlin-processes-geophys.net/12/89/2005/ doi:10.5194/npg-12-89-2005 © Author(s) 2005. This work is licensed under a Creative Commons License. Mixing of rescaled data and Bayesian inference for earthquake recurrence times Grup de Física Estadística, Departament de Física, Facultat de Ciències, Universitat Autònoma de Barcelona, E-08193 Bellaterra, Barcelona, Spain Abstract. The limits of a recently proposed universal scaling law for the probability distributions of earthquake recurrence times are explored. The scaling properties allow to improve the statistics of occurrence of large earthquakes over small areas by mixing rescaled recurrence times for different areas. In this way, the scaling law still holds for events with M≥5.5 at scales of about 20km, and for M≥7.5 at 600km. A Bayesian analysis supports the temporal clustering of seismicity against a description based on nearly-periodic events. The results are valid for stationary seismicity as well as for the nonstationary case, illustrated by the seismicity of Southern California after the Landers earthquake. Full Article (PDF, 795 KB) Special Issue Citation: Corral, A.: Mixing of rescaled data and Bayesian inference for earthquake recurrence times, Nonlin. Processes Geophys., 12, 89-100, doi:10.5194/npg-12-89-2005, 2005. Bibtex EndNote Reference Manager XML |
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