61 research outputs found
Verifying the magnitude dependence in earthquake occurrence
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
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
Features of the earthquake source process simulated by Vere-Jones\u27 branching crack model
Open House, ISM in Tachikawa, 2015.6.19統計数理研究所オープンハウス(立川)、H27.6.19ポスター発
Estimating the maximum earthquake magnitude through short-term earthquake clustering models
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
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
マーク付き点過程の欠損データのテスト及び補完 (Detection and replenishment of missing data for marked point processes)
Open House, ISM in Tachikawa, 2017.6.16統計数理研究所オープンハウス(立川)、H29.6.16ポスター発
震源過程とVere-Jonesの分枝モデル間の類似特性
Open House, ISM in Tachikawa, 2014.6.13統計数理研究所オープンハウス(立川)、H26.6.13ポスター発
A Next-day Earthquake Forecasting Model
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
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