184 citations · 1.1k across the 17 of their papers we have counts for
17 papers
Robust Statistical Tests of Dragon-Kings beyond Power Law Distributions
V. F. Pisarenko, D. Sornette
We ask the question whether it is possible to diagnose the existence of "Dragon-Kings" (DK), namely anomalous observations compared to a power law background distribution of event…
On the Correct Use of Statistical Tests: Reply to "Lies, damned lies and statistics (in Geology)"
D. Sornette, V. Pisarenko
In a Forum published in EOS Transactions AGU (2009) entitled "Lies, damned lies and statistics (in Geology)", Vermeesch (2009) claims that "statistical significant is not the same…
Gibrat's law for cities: uniformly most powerful unbiased test of the Pareto against the lognormal
Y. Malevergne, V. Pisarenko, D. Sornette
We address the general problem of testing a power law distribution versus a log-normal distribution in statistical data. This general problem is illustrated on the distribution of…
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…
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…
Properties of a simple bilinear stochastic model: estimation and predictability
D. Sornette, V. F. Pisarenko
We analyze the properties of arguably the simplest bilinear stochastic multiplicative process, proposed as a model of financial returns and of other complex systems combining both…