Point Processes And Their Statistical Inference
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Point Processes And Their Statistical Inference
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Author : Alan Karr
language : en
Publisher: Routledge
Release Date : 2017-09-06
Point Processes And Their Statistical Inference written by Alan Karr and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-06 with Mathematics categories.
Maintaining the excellent features that made the first edition so popular, this outstanding reference/text presents the only comprehensive treatment of the theory of point processes and statistical inference for point processes-highlighting both pointprocesses on the real line and sp;,.tial point processes. Thoroughly updated and revised to reflect changes since publication of the firstedition, the expanded Second EdiLion now contains a better organized and easierto-understand treatment of stationary point processes ... expanded treatment ofthe multiplicative intensity model ... expanded treatment of survival analysis . ..broadened consideration of applications ... an expanded and extended bibliographywith over 1,000 references ... and more than 3('() end-of-chapter exercises.
Point Processes And Their Statistical Inference
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Author : Alan F. Karr
language : en
Publisher:
Release Date : 1986
Point Processes And Their Statistical Inference written by Alan F. Karr and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Mathematics categories.
Statistical Inference And Simulation For Spatial Point Processes
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Author : Jesper Moller
language : en
Publisher: CRC Press
Release Date : 2003-09-25
Statistical Inference And Simulation For Spatial Point Processes written by Jesper Moller and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-09-25 with Mathematics categories.
Spatial point processes play a fundamental role in spatial statistics and today they are an active area of research with many new applications. Although other published works address different aspects of spatial point processes, most of the classical literature deals only with nonparametric methods, and a thorough treatment of the theory and applications of simulation-based inference is difficult to find. Written by researchers at the top of the field, this book collects and unifies recent theoretical advances and examples of applications. The authors examine Markov chain Monte Carlo algorithms and explore one of the most important recent developments in MCMC: perfect simulation procedures.
Statistical Inference For Spatial Processes
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Author : B. D. Ripley
language : en
Publisher: Cambridge University Press
Release Date : 1988
Statistical Inference For Spatial Processes written by B. D. Ripley and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988 with Mathematics categories.
The study of spatial processes and their applications is an important topic in statistics and finds wide application particularly in computer vision and image processing. This book is devoted to statistical inference in spatial statistics and is intended for specialists needing an introduction to the subject and to its applications. One of the themes of the book is the demonstration of how these techniques give new insights into classical procedures (including new examples in likelihood theory) and newer statistical paradigms such as Monte-Carlo inference and pseudo-likelihood. Professor Ripley also stresses the importance of edge effects and of lack of a unique asymptotic setting in spatial problems. Throughout, the author discusses the foundational issues posed and the difficulties, both computational and philosophical, which arise. The final chapters consider image restoration and segmentation methods and the averaging and summarising of images. Thus, the book will find wide appeal to researchers in computer vision, image processing, and those applying microscopy in biology, geology and materials science, as well as to statisticians interested in the foundations of their discipline.
Semimartingales And Their Statistical Inference
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Author : B.L.S. Prakasa Rao
language : en
Publisher: CRC Press
Release Date : 1999-05-11
Semimartingales And Their Statistical Inference written by B.L.S. Prakasa Rao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-05-11 with Mathematics categories.
Statistical inference carries great significance in model building from both the theoretical and the applications points of view. Its applications to engineering and economic systems, financial economics, and the biological and medical sciences have made statistical inference for stochastic processes a well-recognized and important branch of statistics and probability. The class of semimartingales includes a large class of stochastic processes, including diffusion type processes, point processes, and diffusion type processes with jumps, widely used for stochastic modeling. Until now, however, researchers have had no single reference that collected the research conducted on the asymptotic theory for semimartingales. Semimartingales and their Statistical Inference, fills this need by presenting a comprehensive discussion of the asymptotic theory of semimartingales at a level needed for researchers working in the area of statistical inference for stochastic processes. The author brings together into one volume the state-of-the-art in the inferential aspect for such processes. The topics discussed include: Asymptotic likelihood theory Quasi-likelihood Likelihood and efficiency Inference for counting processes Inference for semimartingale regression models The author addresses a number of stochastic modeling applications from engineering, economic systems, financial economics, and medical sciences. He also includes some of the new and challenging statistical and probabilistic problems facing today's active researchers working in the area of inference for stochastic processes.
Statistical Inference For Spatial Poisson Processes
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Author : Yu A. Kutoyants
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Statistical Inference For Spatial Poisson Processes written by Yu A. Kutoyants and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Mathematics categories.
This work is devoted to several problems of parametric (mainly) and nonparametric estimation through the observation of Poisson processes defined on general spaces. Poisson processes are quite popular in applied research and therefore they attract the attention of many statisticians. There are a lot of good books on point processes and many of them contain chapters devoted to statistical inference for general and partic ular models of processes. There are even chapters on statistical estimation problems for inhomogeneous Poisson processes in asymptotic statements. Nevertheless it seems that the asymptotic theory of estimation for nonlinear models of Poisson processes needs some development. Here nonlinear means the models of inhomogeneous Pois son processes with intensity function nonlinearly depending on unknown parameters. In such situations the estimators usually cannot be written in exact form and are given as solutions of some equations. However the models can be quite fruitful in en gineering problems and the existing computing algorithms are sufficiently powerful to calculate these estimators. Therefore the properties of estimators can be interesting too.
Stochastic Point Processes
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Author : S. Kidambi Srinivasan
language : en
Publisher: Alpha Science Int'l Ltd.
Release Date : 2003
Stochastic Point Processes written by S. Kidambi Srinivasan and has been published by Alpha Science Int'l Ltd. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Mathematics categories.
Stochastic Point Processes are interesting from many points of view. From and abstract point of view, point process is a simple version of random measure; these processes have acquired importance mainly due their viability in modeling a variety of phenomena spanning physical, biological, economic and engineering sciences. This volume with contributions from leading probabilists contains, besides surveys on the state-of-art of the theory, papers dealing with problems of queues, inventory, reliability and population evolution. There are also papers dealing with practical aspects like statistical inference and nonlinear filtering. The book will be of interest to a wide spectrum of people including those working in the area of operations research, signal processing, electrical communications & control and neural network.
An Introduction To The Theory Of Point Processes
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Author : D.J. Daley
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-04-10
An Introduction To The Theory Of Point Processes written by D.J. Daley and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-04-10 with Mathematics categories.
Point 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.
Statistical Inference From Stochastic Processes
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Author : Narahari Umanath Prabhu
language : en
Publisher: American Mathematical Soc.
Release Date : 1988-12-31
Statistical Inference From Stochastic Processes written by Narahari Umanath Prabhu and has been published by American Mathematical Soc. this book supported file pdf, txt, epub, kindle and other format this book has been release on 1988-12-31 with Mathematics categories.
This volume comprises the proceedings of the AMS-IMS-SIAM Summer Research Conference on Statistical Inference from Stochastic Processes, held at Cornell University in August 1987. The conference brought together probabilists and statisticians who have developed important areas of application and made major contributions to the foundations of the subject. Statistical inference from stochastic processes has been important in a number of areas. For example, in applied probability, major advances have been made in recent years in stochastic models arising in science and engineering. However, the emphasis has been on the formulation and analysis of models rather than on the statistical methodology for hypothesis testing and inference. For these models to be of practical use, procedures for their statistical analysis are essential. In the area of probability models, initial work in inference focused on Markov chains, but many models have given rise to non-Markovian and point processes. In recent years, research in statistical inference from such processes not only solved specific problems but also resulted in major contributions to the conceptual framework of the subject as well as the associated techniques. The objective of the conference was to provide the opportunity to survey and evaluate the current state of the art in this area and to discuss future directions. The papers presented covered five topics within the broad domain of inference from stochastic processes: foundations, counting processes and survival analysis, likelihood and its ramifications, applications to statistics and probability models, and processes in economics. Requiring a graduate level background in probability and statistical inference, this book will provide students and researchers with a familiarity with the foundations of inference from stochastic processes and a knowledge of the current developments in this area.
Theory And Modeling Of Stochastic Objects
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Author : Athanasios Christou Micheas
language : en
Publisher: Chapman and Hall/CRC
Release Date : 2015-06-15
Theory And Modeling Of Stochastic Objects written by Athanasios Christou Micheas and has been published by Chapman and Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-15 with Mathematics categories.
This book defines and investigates the concept of a random object. To accomplish this task in a natural way, it brings together three major areas; statistical inference, measure-theoretic probability theory and stochastic processes. This point of view has not been explored by existing textbooks. One would need to use one book on Real Analysis, one on Measure and/or Probability theory, one in Stochastic processes, and at least one on Statistics to capture the detail and depth of material that has gone into this text. The book is targeted towards students at the master's and Ph.D. levels, as well as, academicians in the mathematics, statistics and related disciplines. Basic knowledge of calculus and matrix algebra is required. Prior knowledge of probability or measure theory is welcomed but not necessary.