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20002024
most citedNew Approach to the Characterization of Mmax and of the Tail of the Distribution of Earthquake Magnitudes

61 citations

Showing physics.geo-phShow all

5 papers · 1 filter

physics.geo-ph2022★ 2 cited

Geomagnetic Survey Interpolation with the Machine Learning Approach

Igor Aleshin, Kirill Kholodkov, Ivan Malygin +2

This paper portrays the method of UAV magnetometry survey data interpolation. The method accommodates the fact that this kind of data has a spatial distribution of the samples alon…

physics.geo-ph2021

BitTorrent is Apt for Geophysical Data Collection and Distribution

K. I. Kholodkov, I. M. Aleshin, S. D. Ivanov

This article covers a nouveau idea of how to collect and handle geophysical data with a peer-to-peer network in near real-time. The text covers a brief introduction to the cause, t…

physics.geo-ph2009★ 37 cited

Distribution of Maximum Earthquake Magnitudes in Future Time Intervals, Application to the Seismicity of Japan (1923-2007)

V. F. Pisarenko, D. Sornette, M. V. Rodkin

We modify the new method for the statistical estimation of the tail distribution of earthquake seismic moments introduced by Pisarenko et al. [2009] and apply it to the earthquake…

physics.geo-ph2008★ 2 cited

Characterization of the tail of the distribution of earthquake magnitudes by combining the GEV and GPD descriptions of Extreme Value Theory

V. F. Pisarenko, A. Sornette, D. Sornette +1

We present a generic and powerful approach to study the statistics of extreme phenomena (meteorology, finance, biology...) that we apply to the statistical estimation of the tail o…

physics.geo-ph2007★ 61 cited

New Approach to the Characterization of Mmax and of the Tail of the Distribution of Earthquake Magnitudes

V. F. Pisarenko, A. Sornette, D. Sornette +1

We develop a new method for the statistical esitmation of the tail of the distribution of earthquake sizes recorded in the Worldwide Harvard catalog of seismic moments converted to…