According to the method for predicting strong earthquakes using seismicity patterns,this paper summarizes the seismicity anomalies, generally called anomalous seismicity patterns,as the basis for prediction based on s...According to the method for predicting strong earthquakes using seismicity patterns,this paper summarizes the seismicity anomalies, generally called anomalous seismicity patterns,as the basis for prediction based on some historical data in the Sichuan-Yunnan seismic zone. Using our results,it can be confirmed that these anomaly patterns,which reflect the features of the late stage of strong earthquake preparation process and stress release in the main shock rupture zone,did exist before many earthquake cases. This paper also introduced the characteristics of seismic repeatability and its validation result,and discussed the mechanism of repeatability,which will have an application value for strong earthquake tendency prediction.展开更多
The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><i></i></span><i><span><span><i><span style="...The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><i></i></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate survival functions for arbitrary </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2, 3, </span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;">...</span><span style="font-family:Verdana;">, given all the univariate marginal survival functions. This universal form of </span></span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate probability distributions was obtained by means of “dependence functions” named “joiners” in the text. These joiners determine all the involved stochastic dependencies between the underlying random variables. However, in order that the presented formula (the form) represents a legitimate survival function, some necessary and sufficient conditions for the joiners had to be found. Basically, finding those conditions is the main task of this paper. This task was successfully performed for the case </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> = 2 and the main results for the case </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> = 3 were formulated as Theorem 1 and Theorem 2 in Section 4. Nevertheless, the hypothetical conditions valid for the general </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> ≥ 4 case were also formulated in Section 3 as the (very convincing) Hypothesis. As for the sufficient conditions for both the </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"> = 3 and</span><i> </i></span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> ≥ 4 cases, the full generality was not achieved since two restrictions were imposed. Firstly, we limited ourselves to the, defined in the text, “continuous cases” (when the corresponding joint density exists and is continuous), and secondly we consider positive stochastic dependencies only. Nevertheless, the class of the </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate distributions which can be constructed is very wide. The presented method of construction by means of joiners can be considered competitive to the </span><span style="font-family:Verdana;"><strong></strong></span></span></span><strong><span><span><b><span style="font-family:Verdana;">copula</span></b><span style="font-family:Verdana;"></span></span></span></strong><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> methodology. As it is suggested in the paper the possibility of building a common theory of both copulae and joiners is quite possible, and the joiners may play the role of tools within the theory of copulae, and vice versa copulae may, for example, be used for finding proper joiners. Another independent feature of the joiners methodology is the possibility of constructing many new stochastic processes including stationary and Markovian.</span></span></span>展开更多
文摘According to the method for predicting strong earthquakes using seismicity patterns,this paper summarizes the seismicity anomalies, generally called anomalous seismicity patterns,as the basis for prediction based on some historical data in the Sichuan-Yunnan seismic zone. Using our results,it can be confirmed that these anomaly patterns,which reflect the features of the late stage of strong earthquake preparation process and stress release in the main shock rupture zone,did exist before many earthquake cases. This paper also introduced the characteristics of seismic repeatability and its validation result,and discussed the mechanism of repeatability,which will have an application value for strong earthquake tendency prediction.
文摘The purpose of this paper is to present a general universal formula for <span style="font-family:Verdana;"><i></i></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate survival functions for arbitrary </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> = 2, 3, </span></span></span><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;">...</span><span style="font-family:Verdana;">, given all the univariate marginal survival functions. This universal form of </span></span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate probability distributions was obtained by means of “dependence functions” named “joiners” in the text. These joiners determine all the involved stochastic dependencies between the underlying random variables. However, in order that the presented formula (the form) represents a legitimate survival function, some necessary and sufficient conditions for the joiners had to be found. Basically, finding those conditions is the main task of this paper. This task was successfully performed for the case </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> = 2 and the main results for the case </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> = 3 were formulated as Theorem 1 and Theorem 2 in Section 4. Nevertheless, the hypothetical conditions valid for the general </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> ≥ 4 case were also formulated in Section 3 as the (very convincing) Hypothesis. As for the sufficient conditions for both the </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:;" "=""><span style="font-family:Verdana;"> = 3 and</span><i> </i></span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;"> ≥ 4 cases, the full generality was not achieved since two restrictions were imposed. Firstly, we limited ourselves to the, defined in the text, “continuous cases” (when the corresponding joint density exists and is continuous), and secondly we consider positive stochastic dependencies only. Nevertheless, the class of the </span><span style="font-family:Verdana;"><i></i></span></span></span><i><span><span><i><span style="font-family:Verdana;">k</span></i><span style="font-family:Verdana;"></span></span></span></i><span><span><span style="font-family:Verdana;">-variate distributions which can be constructed is very wide. The presented method of construction by means of joiners can be considered competitive to the </span><span style="font-family:Verdana;"><strong></strong></span></span></span><strong><span><span><b><span style="font-family:Verdana;">copula</span></b><span style="font-family:Verdana;"></span></span></span></strong><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;"> methodology. As it is suggested in the paper the possibility of building a common theory of both copulae and joiners is quite possible, and the joiners may play the role of tools within the theory of copulae, and vice versa copulae may, for example, be used for finding proper joiners. Another independent feature of the joiners methodology is the possibility of constructing many new stochastic processes including stationary and Markovian.</span></span></span>