46 research outputs found

    Verifying the magnitude dependence in earthquake occurrence

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    The existence of magnitude dependence in earthquake triggering has been reported. Such a correlation is linked to the issue of seismic predictability and remains under intense debate whether it is physical or is caused by incomplete data due to short-term aftershocks missing. Working firstly with a synthetic catalogue generated by a numerical model that capture most statistical features of earthquakes and then with an high-resolution earthquake catalogue for the Amatrice-Norcia (2016) sequence in Italy, where for the latter case we employ the stochastic declustering method to reconstruct the family tree among seismic events and limit our analysis to events above the magnitude of completeness, we found that the hypothesis of magnitude correlation can be rejected

    A parimutuel gambling perspective to compare probabilistic seismicity forecasts

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    Using analogies to gaming, we consider the problem of comparing multiple probabilistic seismicity forecasts. To measure relative model performance, we suggest a parimutuel gambling perspective which addresses shortcomings of other methods such as likelihood ratio, information gain and Molchan diagrams. We describe two variants of the parimutuel approach for a set of forecasts: head-to-head, in which forecasts are compared in pairs, and round table, in which all forecasts are compared simultaneously. For illustration, we compare the 5-yr forecasts of the Regional Earthquake Likelihood Models experiment for M4.95+ seismicity in Californi

    Estimating the maximum earthquake magnitude through short-term earthquake clustering models

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    Open House, ISM in Tachikawa, 2012.6.15統計数理研究所オープンハウス(立川)、H24.6.15ポスター発

    Risk and return: evaluating Reverse Tracing of Precursors earthquake predictions

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    In 2003, the Reverse Tracing of Precursors (RTP) algorithm attracted the attention of seismologists and international news agencies when researchers claimed two successful predictions of large earthquakes. These researchers had begun applying RTP to seismicity in Japan, California, the eastern Mediterranean and Italy; they have since applied it to seismicity in the northern Pacific, Oregon and Nevada. RTP is a pattern recognition algorithm that uses earthquake catalogue data to declare alarms, and these alarms indicate that RTP expects a moderate to large earthquake in the following months. The spatial extent of alarms is highly variable and each alarm typically lasts 9 months, although the algorithm may extend alarms in time and space. We examined the record of alarms and outcomes since the prospective application of RTP began, and in this paper we report on the performance of RTP to date. To analyse these predictions, we used a recently developed approach based on a gambling score, and we used a simple reference model to estimate the prior probability of target earthquakes for each alarm. Formally, we believe that RTP investigators did not rigorously specify the first two ‘successful' predictions in advance of the relevant earthquakes; because this issue is contentious, we consider analyses with and without these alarms. When we included contentious alarms, RTP predictions demonstrate statistically significant skill. Under a stricter interpretation, the predictions are marginally unsuccessfu

    A Next-day Earthquake Forecasting Model

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    Open House, ISM in Tachikawa, 2011.7.14統計数理研究所オープンハウス(立川)、H23.7.14ポスター発