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研究生:謝侑霖
研究生(外文):Yu-Lin Hsieh
論文名稱:2019 年美國加州規模 7.1 里奇克萊斯特地震之餘震風險統計評估
指導教授:陳玉英陳玉英引用關係
指導教授(外文):Yuh-Ing Chen
學位類別:碩士
校院名稱:國立中央大學
系所名稱:統計研究所
學門:數學及統計學門
學類:統計學類
論文出版年:2020
畢業學年度:108
語文別:中文
論文頁數:66
中文關鍵詞:餘震時空規模風險模式混合分布接收者操作特徵曲線相對餘震風險圖
外文關鍵詞:Space-time-magnitude aftershock hazard modelmixture distributionreceiver operating characteristic curverelative aftershock hazard map
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強烈主震後經常引起大量餘震,短時間內發生的大規模餘震可能會破壞震區已經弱化的建物或結構,因此餘震風險評估對於主震後短時間內的救援行動極為重要。本文分別利用混合二元常態分布與混合迦馬結合條件常態分布描述餘震的空間分布,並且結合餘震規模時間風險模型(Reasenberg and Jones, 1898, 1994),建立餘震規模時空風險模型,分別記為BNSRJ與GNSRJ模型,分析2019年規模7.1的美國加州里奇克萊斯特地震之餘震風險。根據在里奇克萊斯特主震後一段時間內的完整餘震,應用BNSRJ與GNSRJ模型或是RJ模型結合點格法(GRJ)計算研究中點格的餘震相對風險,建立相對餘震風險圖用於預警未來等長時間強餘震發生的可能區域。最後藉由接收者操作特徵(ROC)曲線相關的準則評估上述相對餘震風險圖在預警未來大餘震的表現。根據ROC曲線下面積(AUC)評估,應用BNSRJ及GNSRJ模型所建立的相對餘震風險圖在主震後3及6小時預警規模4.0以上餘震的效果皆優於GRJ,在12小時預警未來規模4.0以上餘震區域時,則以GNSRJ最優。但是,在主震後24小時因為餘震數量多,研究中的三種相對餘震風險圖之餘震效果無差異。最後,Youden 指數建議GNSRJ的相對風險門檻值設在0.05與0.15之間,才能在里奇克萊斯特主震後的3~12小時內有效預警未來規模4.0以上餘震區域。
A strong earthquake often brings up a lot of aftershocks. Large aftershocks that occur in a short time after the main shock may damage the weakened buildings or structures. Therefore, assessment of aftershock hazard is extremely important for rescue work within a short time after the main shock. In this article, we use the mixture bivariate normal distribution and the mixture gamma along with conditional normal distribution, respectively, to describe the spatial distribution of aftershocks. By combining the spatial distribution with the magnitude-time hazard model of aftershocks (Reasenberg and Jones, 1898, 1994), the two space-time-magnitude hazard models of aftershocks are then obtained, denoted as BNSRJ and GNSRJ models, respectively. The BNSRJ or GNSRJ are then applied to analyze the hazard of aftershocks of the 2019 Ridgecrest earthquake in the United States. Based on the completely recorded aftershocks in a short period after the main shock, relative hazard of aftershocks in each period under study is calculated by using the BNSRJ, GNSRJ or RJ models with the gridding method (GRJ). The relative aftershock hazard (RAH) maps are then obtained for depicting possible areas of future large aftershocks. Finally, the performance of RAH maps for alarming large aftershocks in a short time after the main shock is evaluated based on criterion related to the receiver operating characteristic (ROC) curve. Based on the area under the ROC curve (AUC), RAH maps based on the BNSRJ and GNSRJ models are better than the GRJ map for alarming 4.0 or larger aftershocks in 3 to 6 hours after the main shock. The GNSRJ map is superior to the other two when alarming such aftershocks in 12 hours after the main shock. However, the three RAH maps are of no difference when alarming future aftershocks in one day after the main shock. Finally, Youden’s index suggests threshold between 0.05 and 0.15 for the relative aftershock hazard to effectively depict the possible area of future 4.0 aftershocks.
摘要 i
Abstract ii
致謝辭 iv
目錄 v
圖目錄 vii
表目錄 viii
一、 研究動機與目的 1
二、 文獻回顧 6
2.1 地震規模頻率模型 6
2.2 餘震衰退模型 8
2.3 餘震規模-時間風險模型 10
2.4 餘震空間風險模式 11
2.5 餘震的空間風險圖及其預警效果評估 12
三、 研究方法 16
3.1 RJ模型適用性檢定 16
3.2 餘震空間風險模型 17
3.2.1 餘震空間分布 17
3.2.2 空間分布參數估計 18
3.3 餘震時空規模風險模型 20
四、 資料分析 23
4.1 RJ模型分析 24
4.2 餘震時空規模分析 25
4.3 分析結果討論 26
五、 結論 29
參考文獻 30
Aki, K. (1965). Maximum likelihood estimate of in the formula and its confidence limits. Bulletin of the Earthquake Research Institute, 43: 237–
239.
Bamber, D. (1975). The area above the ordinal dominance graph and the area below the
receiver operating characteristic graph. Journal of Mathematical Psychology, 12(4), 387-415.
Best, D. J., Gipps, P. G. (1974). Algorithm AS 71: The upper tail probabilities of Kendall’s tau. Applied Statistics,23, 98–100.
Chen, Y. I., Huang, C. S., & Liu, J. Y. (2015a). Statistical analysis of earthquakes after the 1999 MW 7.7 Chi-Chi, Taiwan, earthquake based on a modified Reasenberg–Jones model. Journal of Asian Earth Sciences, 114, 299-304.
Chen, Y. I., Liu, J. Y. and Lai, H. W. (2020). Assessment of Space–Time Hazard of Large Aftershocks of the 2008 Mw7.9 Wenchuan Earthquake. Pure and Applied Geophysics, 177, 27-36.
Chen, F., Xue, Y., Tan, M. T., & Chen, P. (2015b). Efficient statistical tests to compare Youden index: accounting for contingency correlation. Statistics in Medicine, 34(9), 1560-1576.
Dempster, A. P., Laird, N. M., and Rubin, D. B. (1977). Maximum Likelihood from Incomplete Data via the EM Algorithm. Journal of the Royal Statistical Society, Series B. 39(1): 1–38
Gerstenberger, M., Wiemer, S. , Jones, L. M. and Reasenber, P. A. (2005). Real-time forecasts of tomorrow’s earthquakes in California. Nature, 435(7074), 328–331.
Gerstenberger, M., Jones, L. M. and Wiemer, S. (2007). Short-term aftershock probabilities: case studies in California. Seismological Research Letters,78(1), 66-77.
Gutenberg, R. and Richter, C. F. (1944). Frequency of earthquakes in California. Bulletin of the Seismological Society of America, 34, 185–188.
Hartigan, J. A. and Wong, M. A. (1979). Algorithm AS 136: A k-Means Clustering Algorithm. Journal of the Royal Statistical Society, Series C. 28 (1), 100–108.
Kendall, M. (1938). A New Measure of Rank Correlation. Biometrika. 30, 81–89.
Kolmogorov, A. (1933). Sulla determinazione empirica di una lgge di distribuzione. Giornale dell'Istituto Italiano degli Attuari, 4, 83-91.
Lusted, L. B. (1960). Logical analysis in roentgen diagnosis: memorial fund lecture. Radiology, 74(2), 178-193.
Ogata, Y. (1983). Estimation of the parameters in the modified 359 Omori formula for aftershock sequences by the maximum likelihood procedure. Journal of Physics of the Earth, 31, 115–124.
Ogata, Y. (1988). Statistical models for earthquake occurrences and residual analysis for point processes, Journal of the American Statistical Association, 83, 9–27.
Ogata, Y. (1998). Space-time point-process models for earthquake occurrences, Annals of the Institute of Statistical Mathematics, 50, no. 2, 379–402.
Omori, F. (1894). On the aftershocks of earthquake. Journal of the College of Science, Imperial University of Tokyo, 7, 111–200.
Parzen, E. (1962). "On Estimation of a Probability Density Function and Mode". The Annals of Mathematical Statistics. 33 (3): 1065–1076.
Reasenberg, P. A. and Jones, L. M. (1989). Earthquake hazard after a mainshock in California. Science, 243, 1173–1176.
Reasenberg, P. A. and Jones, L. M. (1994). Earthquake aftershocks:update. Science, 265, 1251–1252.
Rosenblatt, M. (1956). "Remarks on Some Nonparametric Estimates of a Density Function". The Annals of Mathematical Statistics. 27 (3): 832–837.
Sarlis, N. V., and Christopoulos, S. R. G. (2014). Visualization of the significance of receiver operating characteristics based on confidence ellipses. Computer Physics Communications, 185, 1172–1176.
Shi, Y. and Bolt, B. A.(1982). The standard error of the magnitude-frequency b value. Bulletin of the Seismological Society of America, 72 (5), 1677–1687.
Smith, W. D. (1981). The b-value as an earthquake precursor. Nature, 289(5794), 136–139.
Swets, J.(1988). Measuring the accuracy of diagnostic systems. Science, 240, 1285–1293.
Utsu, T. (1961). A statistical study on the occurrence of aftershocks. Geophysical Magazine, 30(4), 521–605.
Utsu, T., Ogata, Y. and Matsuura, R. S. (1995). The centenary of the Omori formula for a decay law of aftershock activity. Journal of Physics of the Earth, 43(1), 1– 33.
Wiemer, S. and Katsumata, K. (1999). Spatial variability of seismicity parameters in aftershock zones. Journal of Geophysical Research, 104(b6), 13135–13151
Wiemer, S. and Wyss, M. (1997). Mapping the frequency-magnitude distribution in asperities; an improved technique to calculate recurrence times? Journal of Geophysical Research, 102(b7), 15115–15128.
Wiemer, S. and Wyss, M. (2000). Minimum magnitude of completeness in earthquake catalogs: Examples from Alaska, the western US and Japan. Bulletin of the Seismological Society of America, 90, 859–869.
Wiemer, S. (2000). Introducing probabilistic aftershock hazard mapping. Geophysical Research Letters, 27, 3405–3408.
Youden, W. J. (1950). Index for rating diagnostic tests. Cancer, 3(1), 32-35.
Zhuang, J., Ogata, Y., Vere-Jones, D., (2002). Stochastic declustering of space–time earthquake occurrences. Journal of the American Statistical Association, 97, 369 – 380.
簡子軒(2019),「多板塊交界地區餘震時空風險之統計評估」,國立中央大學,碩士論文。
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