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Point Processes and Their Statistical Inference

2017-09-06 Mathematics
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Release : 2017-09-06
Genre : Mathematics
Kind : eBook
Book Rating : 835/5 ( reviews)

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Book Synopsis Point Processes and Their Statistical Inference by : Alan Karr

Download or read book Point Processes and Their Statistical Inference written by Alan Karr. This book was released on 2017-09-06. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Statistical Inference and Simulation for Spatial Point Processes

2003-09-25 Mathematics
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Release : 2003-09-25
Genre : Mathematics
Kind : eBook
Book Rating : 930/5 ( reviews)

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Book Synopsis Statistical Inference and Simulation for Spatial Point Processes by : Jesper Moller

Download or read book Statistical Inference and Simulation for Spatial Point Processes written by Jesper Moller. This book was released on 2003-09-25. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Point Processes and Their Statistical Inference

1986 Mathematics
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Release : 1986
Genre : Mathematics
Kind : eBook
Book Rating : /5 ( reviews)

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Book Synopsis Point Processes and Their Statistical Inference by : Alan F. Karr

Download or read book Point Processes and Their Statistical Inference written by Alan F. Karr. This book was released on 1986. Available in PDF, EPUB and Kindle. Book excerpt:

Point Processes And Their Statistical Inference

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Genre :
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Book Synopsis Point Processes And Their Statistical Inference by : A.F. Karr

Download or read book Point Processes And Their Statistical Inference written by A.F. Karr. This book was released on . Available in PDF, EPUB and Kindle. Book excerpt:

Statistical Inference for Spatial Poisson Processes

2012-12-06 Mathematics
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Release : 2012-12-06
Genre : Mathematics
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Book Rating : 067/5 ( reviews)

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Book Synopsis Statistical Inference for Spatial Poisson Processes by : Yu A. Kutoyants

Download or read book Statistical Inference for Spatial Poisson Processes written by Yu A. Kutoyants. This book was released on 2012-12-06. Available in PDF, EPUB and Kindle. Book excerpt: 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.

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