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The goal of this paper is to derive a hazard map for earthquake occurrences in Pakistan from a catalogue that contains spatial coordinates of shallow earthquakes of magnitude 4.5 or larger aggregated over calendar years. We test relative temporal stationarity by the KPSS statistic and use the inhomogeneous J -function to test for inter-point interactions. We then formulate a cluster model, and de-convolve in order to calculate the hazard map, and verify that no particular year has an undue influence on the map. Within the borders of the single country, the KPSS test did not show any deviation from homogeneity in the spatial intensities. The inhomogeneous J -function indicated clustering that could not be attributed to inhomogeneity, and the analysis of aftershocks showed some evidence of two major shocks instead of one during the 2005 Kashmir earthquake disaster. Thus, the spatial point pattern analysis carried out for these data was insightful in various aspects and the hazard map that was obtained may lead to improved measures to protect the population against the disastrous effects of earthquakes.

We consider a sequence of Poisson cluster point processes on $\\mathbb{R}^d$ : at step $n\\in\\mathbb{N}_0$ of the construction, the cluster centers have intensity $c/(n+1)$ for some $c>0$ , and each cluster consists of the particles of a branching random walk up to generation n—generated by a point process with mean 1. We show that this ‘critical cluster cascade’ converges weakly, and that either the limit point process equals the void process (extinction), or it has the same intensity c as the critical cluster cascade (persistence). We obtain persistence if and only if the Palm version of the outgrown critical branching random walk is locally almost surely finite. This result allows us to give numerous examples for persistent critical cluster cascades.

We introduce a new point process, the dynamic contagion process, by generalising the Hawkes process and the Cox process with shot noise intensity. Our process includes both self-excited and externally excited jumps, which could be used to model the dynamic contagion impact from endogenous and exogenous factors of the underlying system. We have systematically analysed the theoretical distributional properties of this new process, based on the piecewise-deterministic Markov process theory developed in Davis (1984), and the extension of the martingale methodology used in Dassios and Jang (2003). The analytic expressions of the Laplace transform of the intensity process and the probability generating function of the point process have been derived. An explicit example of specified jumps with exponential distributions is also given. The object of this study is to produce a general mathematical framework for modelling the dependence structure of arriving events with dynamic contagion, which has the potential to be applicable to a variety of problems in economics, finance, and insurance. We provide an application of this process to credit risk, and a simulation algorithm for further industrial implementation and statistical analysis.

This paper studies a generalized cumulative shock model with a cluster shock structure. The system considered is subject to two types of shocks, called primary shocks and secondary shocks, where each primary shock causes a series of secondary shocks. The lifetime behavior of such a system becomes more complicated than that of a classical model with only one class of shocks. Under a non-homogeneous Poisson process of primary shocks, we analyze the lifetime behavior of the system with light-tailed and heavy-tailed distributed secondary shocks. We show some important characteristics of lifetime of this type of system. Our model, as an extension of the classical shock models, has wide applications in maintenance engineering, operations management, and insurance risk assessment.

The goal of this paper is to investigate the tools of extreme value theory originally introduced for discrete time stationary stochastic processes (time series), namely the tail process and the tail measure, in the framework of continuous time stochastic processes with paths in the space D of càdlàg functions indexed by ℝ, endowed with Skorohod’s J1 topology. We prove that the essential properties of these objects are preserved, with some minor (though interesting) differences arising. We first obtain structural results which provide representation for homogeneous shift-invariant measures on D and then study regular variation of random elements in D. We give practical conditions and study several examples, recovering and extending known results.

The use of properties of a Poisson process to study the randomness of stars is traced back to a 1767 paper. The process was used and rediscovered many times, and we mention some of the early scientific areas. The name Poisson process was first used in print in 1940, and we believe the term was coined in the corridors of Stockholm University some time between 1936 and 1939. We follow the early developments of doubly stochastic processes and cluster processes, and describe different efforts to apply the Markov property to point processes. Le recours aux processus de Poisson dans l'étude de la distribution des étoiles remonte à une publication de 1767. Ce type de processus a été redécouvert et utilisé à maintes reprises, et nous mentionnons quelques-uns des domaines scientifiques où il l'a été pour la première fois. La première trace imprimée du nom \"processus de Poisson\" apparaît en 1940, et nous pensons que cette terminologie est née dans les couloirs de l'Université de Stockholm entre 1936 et 1939. Nous retraçons les premiers développements des processus doublement stochastiques et des processus de Poisson en grappes, et décrivons les efforts accomplis en vue d'appliquer aux processus ponctuels la propriété de Markov.

For Gaussian stationary triangular arrays, it is well known that the extreme values may occur in clusters. Here we consider the joint behaviors of the point processes of clusters and the partial sums of bivariate stationary Gaussian triangular arrays. For a bivariate stationary Gaussian triangular array, we derive the asymptotic joint behavior of the point processes of clusters and prove that the point processes and partial sums are asymptotically independent. As an immediate consequence of the results, one may obtain the asymptotic joint distributions of the extremes and partial sums. We illustrate the theoretical findings with a numeric example.

In this paper, we propose a theoretical framework to analyze the performance of ultra wideband acquisition （UWB） system based on energy detection （ED） over IEEE 802.15.3a channel. The proposed framework enables to calculate probability density function （PDF） of square-sum of multipath components （MPCs） gain collected by receiver, and the averaged criteria. In particular, the expectation and variance of the sum variant characterized approximately by log-normal distribution are expressed in a closed form based on cluster point process. Moreover, the calculating methods of averaged criteria, through Markov chain model and signal flow graph, are clearly demonstrated for different applicable scenarios. The proposed framework is well consistent with simulation results with respect to each calculation method.

We consider a system of independent branching random walks on R which start from a Poisson point process with intensity of the form e λ(du) = e-λu du, where λ ∈ R is chosen in such a way that the overall intensity of particles is preserved. Denote by χ the cluster distribution, and let φ be the log-Laplace transform of the intensity of χ. If λφ'(λ) > 0, we show that the system is persistent, meaning that the point process formed by the particles in the nth generation converges as n → ∞ to a non-trivial point process Πeλ χ with intensity e λ. If λφ'(λ) < 0 then the branching population suffers local extinction, meaning that the limiting point process is empty. We characterize point processes on R which are cluster invariant with respect to the cluster distribution χ as mixtures of the point processes Π ce λ χ over c > 0 and λ ∈ K st, where K st = {λ ∈ R: φ(λ) = 0, λφ'(λ) > 0}.

A new point process is proposed which can be viewed either as a Boolean cluster model with two cluster modes or as a p-thinned Neyman-Scott cluster process with the retention of the original parent point. Voronoi tessellation generated by such a point process has extremely high coefficients of variation of cell volumes as well as of profile areas and lengths in the planar and line induced tessellations. An approximate numerical model of tessellation characteristics is developed for the case of small cluster size; its predictions are compared with the results of computer simulations. Tessellations of this type can be used as models of grain structures in steels.[PUBLICATION ABSTRACT]