Anisotropic Extensions of Space-time Point Process Models for Earthquake Occurrences
Author: Ka Leung Wong
Publisher:
Published: 2009
Total Pages: 144
ISBN-13:
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Author: Ka Leung Wong
Publisher:
Published: 2009
Total Pages: 144
ISBN-13:
DOWNLOAD EBOOKAuthor: Ann Chu
Publisher:
Published: 2009
Total Pages: 150
ISBN-13:
DOWNLOAD EBOOKAuthor: Eric Warren Fox
Publisher:
Published: 2015
Total Pages: 100
ISBN-13:
DOWNLOAD EBOOKSelf-exciting point processes describe random sequences of events where the occurrence of an event increases the likelihood that subsequent events occur nearby in time and space. Models for self-exciting point processes have many important applications to diverse topics such as earthquake and crime forecasting, epidemiology, invasive species, and social networks. The first part of this dissertation discusses a new application of self-exciting point processes to modeling the times when e-mails are sent by individuals in a social network. The proposed models are fit to datasets from West Point Military Academy and the Enron Corporation, and the resulting parameter estimates characterize communication behaviors and leadership roles for users in each network. We argue that the self-exciting models adequately capture major temporal clustering features in the data and perform better than traditional stationary Poisson models. The second part of this dissertation discusses the nonparametric method of Marsan and Lengline (2008) for estimating space-time Hawkes point process models of earthquake occurrences. Their method provides an estimate of a stationary background rate for mainshocks, and a histogram estimate of the triggering function for the rate of aftershocks following an earthquake. At each step of the procedure the model estimates rely on computing the probability each earthquake is a mainshock or aftershock of a previous event. We focus on improving Marsan and Lengline's method by proposing novel ways to incorporate a non-stationary background rate, and adding error bars to the histogram estimates which capture the sampling variability and bias in the estimation of the underlying seismic process. A simulation study is designed to validate and assess new methodology. An application to earthquake data from the Tohoku District in Japan is also discussed, and the results are compared to a well established parametric model of seismicity for this region.
Author: Rodolfo Console
Publisher: John Wiley & Sons
Published: 2017-07-17
Total Pages: 141
ISBN-13: 1119372224
DOWNLOAD EBOOKEarthquake Occurrence provides the reader with a review of algorithms applicable for modeling seismicity, such as short-term earthquake clustering and pseudo-periodic long-term behavior of major earthquakes. The concept of the likelihood ratio of a set of observations under different hypotheses is applied for comparison among various models. In short-term models, known by the term ETAS, the occurrence space and time rate density of earthquakes is modeled as the sum of two terms, one representing the independent or spontaneous events, and the other representing the activity triggered by previous earthquakes. Examples of the application of such algorithms in real cases are also reported. Dealing with long-term recurrence models, renewal time-dependent models, implying a pseudo-periodicity of earthquake occurrence, are compared with the simple time-independent Poisson model, in which every event occurs regardless of what has occurred in the past. The book also introduces a number of computer codes developed by the authors over decades of seismological research.
Author:
Publisher:
Published: 2003
Total Pages: 1146
ISBN-13:
DOWNLOAD EBOOKA scientific and educational journal not only for professional statisticians but also for economists, business executives, research directors, government officials, university professors, and others who are seriously interested in the application of statistical methods to practical problems, in the development of more useful methods, and in the improvement of basic statistical data.
Author: D.J. Daley
Publisher: Springer Science & Business Media
Published: 2006-04-10
Total Pages: 487
ISBN-13: 0387215646
DOWNLOAD EBOOKPoint processes and random measures find wide applicability in telecommunications, earthquakes, image analysis, spatial point patterns, and stereology, to name but a few areas. The authors have made a major reshaping of their work in their first edition of 1988 and now present their Introduction to the Theory of Point Processes in two volumes with sub-titles Elementary Theory and Models and General Theory and Structure. Volume One contains the introductory chapters from the first edition, together with an informal treatment of some of the later material intended to make it more accessible to readers primarily interested in models and applications. The main new material in this volume relates to marked point processes and to processes evolving in time, where the conditional intensity methodology provides a basis for model building, inference, and prediction. There are abundant examples whose purpose is both didactic and to illustrate further applications of the ideas and models that are the main substance of the text.
Author: Alejandro Veen
Publisher:
Published: 2006
Total Pages: 166
ISBN-13: 9780542901522
DOWNLOAD EBOOKThe third part of this work applies the weighted K-function to assess the goodnessof-fit of a class of point process models for the spatial distribution of earthquakes in Southern California. Then, the proposed EM-type algorithm is used to estimate declustered background seismicity rates of geologically distinct regions in Southern California.
Author: Nikolaos Limnios
Publisher: John Wiley & Sons
Published: 2021-03-31
Total Pages: 336
ISBN-13: 1119825032
DOWNLOAD EBOOKThe study of earthquakes is a multidisciplinary field, an amalgam of geodynamics, mathematics, engineering and more. The overriding commonality between them all is the presence of natural randomness. Stochastic studies (probability, stochastic processes and statistics) can be of different types, for example, the black box approach (one state), the white box approach (multi-state), the simulation of different aspects, and so on. This book has the advantage of bringing together a group of international authors, known for their earthquake-specific approaches, to cover a wide array of these myriad aspects. A variety of topics are presented, including statistical nonparametric and parametric methods, a multi-state system approach, earthquake simulators, post-seismic activity models, time series Markov models with regression, scaling properties and multifractal approaches, selfcorrecting models, the linked stress release model, Markovian arrival models, Poisson-based detection techniques, change point detection techniques on seismicity models, and, finally, semi-Markov models for earthquake forecasting.
Author: James Molyneux
Publisher:
Published: 2018
Total Pages: 92
ISBN-13:
DOWNLOAD EBOOKPoint processes have long been used as an effective modeling technique in the forecasting of earthquakes. In this dissertation, we evaluate the ability of earthquake focal mechanisms to predict the locational direction of future events and the usefulness of more complicated point process models including such covariates. We also introduce a new computational method for estimating parameters of point processes models using the Stoyan-Grabarnik estimator which avoids the need to numerically compute the intractable integral term needed to compute estimates via maximum likelihood.
Author: Robert Alan Clements
Publisher:
Published: 2011
Total Pages: 196
ISBN-13:
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