Statistical Parametric Mapping: The Analysis of Functional Brain Images

Statistical Parametric Mapping: The Analysis of Functional Brain Images
A Book

by William D. Penny,Karl J. Friston,John T. Ashburner,Stefan J. Kiebel,Thomas E. Nichols

  • Publisher : Elsevier
  • Release : 2011-04-28
  • Pages : 656
  • ISBN : 0080466508
  • Language : En, Es, Fr & De
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In an age where the amount of data collected from brain imaging is increasing constantly, it is of critical importance to analyse those data within an accepted framework to ensure proper integration and comparison of the information collected. This book describes the ideas and procedures that underlie the analysis of signals produced by the brain. The aim is to understand how the brain works, in terms of its functional architecture and dynamics. This book provides the background and methodology for the analysis of all types of brain imaging data, from functional magnetic resonance imaging to magnetoencephalography. Critically, Statistical Parametric Mapping provides a widely accepted conceptual framework which allows treatment of all these different modalities. This rests on an understanding of the brain's functional anatomy and the way that measured signals are caused experimentally. The book takes the reader from the basic concepts underlying the analysis of neuroimaging data to cutting edge approaches that would be difficult to find in any other source. Critically, the material is presented in an incremental way so that the reader can understand the precedents for each new development. This book will be particularly useful to neuroscientists engaged in any form of brain mapping; who have to contend with the real-world problems of data analysis and understanding the techniques they are using. It is primarily a scientific treatment and a didactic introduction to the analysis of brain imaging data. It can be used as both a textbook for students and scientists starting to use the techniques, as well as a reference for practicing neuroscientists. The book also serves as a companion to the software packages that have been developed for brain imaging data analysis. An essential reference and companion for users of the SPM software Provides a complete description of the concepts and procedures entailed by the analysis of brain images Offers full didactic treatment of the basic mathematics behind the analysis of brain imaging data Stands as a compendium of all the advances in neuroimaging data analysis over the past decade Adopts an easy to understand and incremental approach that takes the reader from basic statistics to state of the art approaches such as Variational Bayes Structured treatment of data analysis issues that links different modalities and models Includes a series of appendices and tutorial-style chapters that makes even the most sophisticated approaches accessible

Neuroscience Databases

Neuroscience Databases
A Practical Guide

by Rolf Kötter

  • Publisher : Springer Science & Business Media
  • Release : 2012-12-06
  • Pages : 310
  • ISBN : 1461510791
  • Language : En, Es, Fr & De
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Neuroscience Databases: A Practical Guide is the first book providing a comprehensive overview of these increasingly important databases. This volume makes the results of the Human Genome Project and other recent large-scale initiatives in the neurosciences available to a wider community. It extends the scope of bioinformatics from the molecular to the cellular, microcircuitry and systems levels, dealing for the first time with complex neuroscientific issues and leading the way to a new culture of data sharing and data mining necessary to successfully tackle neuroscience questions. Aimed at the novice user who wants to access the data, it provides clear and concise instructions on how to download the available data sets and how to use the software with a minimum of technical detail with most chapters written by the database creators themselves.

Handbook of Mathematical Geosciences

Handbook of Mathematical Geosciences
Fifty Years of IAMG

by B.S. Daya Sagar,Qiuming Cheng,Frits Agterberg

  • Publisher : Springer
  • Release : 2018-06-25
  • Pages : 914
  • ISBN : 3319789996
  • Language : En, Es, Fr & De
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This Open Access handbook published at the IAMG's 50th anniversary, presents a compilation of invited path-breaking research contributions by award-winning geoscientists who have been instrumental in shaping the IAMG. It contains 45 chapters that are categorized broadly into five parts (i) theory, (ii) general applications, (iii) exploration and resource estimation, (iv) reviews, and (v) reminiscences covering related topics like mathematical geosciences, mathematical morphology, geostatistics, fractals and multifractals, spatial statistics, multipoint geostatistics, compositional data analysis, informatics, geocomputation, numerical methods, and chaos theory in the geosciences.

Human Brain Function

Human Brain Function
A Book

by Karl J. Friston,Christopher D. Frith,Raymond J. Dolan,Cathy J. Price,Semir Zeki,John T. Ashburner,William D. Penny

  • Publisher : Elsevier
  • Release : 2004-01-26
  • Pages : 1144
  • ISBN : 9780080472959
  • Language : En, Es, Fr & De
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This updated second edition provides the state of the art perspective of the theory, practice and application of modern non-invasive imaging methods employed in exploring the structural and functional architecture of the normal and diseased human brain. Like the successful first edition, it is written by members of the Functional Imaging Laboratory - the Wellcome Trust funded London lab that has contributed much to the development of brain imaging methods and their application in the last decade. This book should excite and intrigue anyone interested in the new facts about the brain gained from neuroimaging and also those who wish to participate in this area of brain science. * Represents an almost entirely new book from 1st edition, covering the rapid advances in methods and in understanding of how human brains are organized * Reviews major advances in cognition, perception, emotion and action * Introduces novel experimental designs and analytical techniques made possible with fMRI, including event-related designs and non-linear analysis

Handbook of Functional MRI Data Analysis

Handbook of Functional MRI Data Analysis
A Book

by Russell A. Poldrack,Jeanette A. Mumford,Thomas E. Nichols

  • Publisher : Cambridge University Press
  • Release : 2011-08-22
  • Pages : 329
  • ISBN : 1139498363
  • Language : En, Es, Fr & De
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Functional magnetic resonance imaging (fMRI) has become the most popular method for imaging brain function. Handbook of Functional MRI Data Analysis provides a comprehensive and practical introduction to the methods used for fMRI data analysis. Using minimal jargon, this book explains the concepts behind processing fMRI data, focusing on the techniques that are most commonly used in the field. This book provides background about the methods employed by common data analysis packages including FSL, SPM and AFNI. Some of the newest cutting-edge techniques, including pattern classification analysis, connectivity modeling and resting state network analysis, are also discussed. Readers of this book, whether newcomers to the field or experienced researchers, will obtain a deep and effective knowledge of how to employ fMRI analysis to ask scientific questions and become more sophisticated users of fMRI analysis software.

fMRI

fMRI
Basics and Clinical Applications

by Stephan Ulmer,Olav Jansen

  • Publisher : Springer Science & Business Media
  • Release : 2013-06-12
  • Pages : 325
  • ISBN : 3642343422
  • Language : En, Es, Fr & De
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Over the past two decades, fMRI has evolved into an invaluable clinical tool for routine brain imaging. This book provides a state of the art overview of fMRI and its use in clinical practice. Experts in the field share their knowledge and explain how to overcome diverse potential technical barriers and problems. Starting from the very basics on the origin of the BOLD signal, the book covers technical issues, anatomical landmarks, the full range of clinical applications, methods of statistical analysis, and special issues in various clinical fields. Comparisons are made with other brain mapping techniques, such as DTI, PET, TMS, EEG, and MEG, and their combined use with fMRI is also discussed. Since the first edition, original chapters have been updated and new chapters added, covering both novel aspects of analysis and further important clinical applications.

Magnetic Resonance Brain Imaging

Magnetic Resonance Brain Imaging
Modeling and Data Analysis Using R

by Jörg Polzehl,Karsten Tabelow

  • Publisher : Springer Nature
  • Release : 2019-09-25
  • Pages : 231
  • ISBN : 3030291847
  • Language : En, Es, Fr & De
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This book discusses the modeling and analysis of magnetic resonance imaging (MRI) data acquired from the human brain. The data processing pipelines described rely on R. The book is intended for readers from two communities: Statisticians who are interested in neuroimaging and looking for an introduction to the acquired data and typical scientific problems in the field; and neuroimaging students wanting to learn about the statistical modeling and analysis of MRI data. Offering a practical introduction to the field, the book focuses on those problems in data analysis for which implementations within R are available. It also includes fully worked examples and as such serves as a tutorial on MRI analysis with R, from which the readers can derive their own data processing scripts. The book starts with a short introduction to MRI and then examines the process of reading and writing common neuroimaging data formats to and from the R session. The main chapters cover three common MR imaging modalities and their data modeling and analysis problems: functional MRI, diffusion MRI, and Multi-Parameter Mapping. The book concludes with extended appendices providing details of the non-parametric statistics used and the resources for R and MRI data.The book also addresses the issues of reproducibility and topics like data organization and description, as well as open data and open science. It relies solely on a dynamic report generation with knitr and uses neuroimaging data publicly available in data repositories. The PDF was created executing the R code in the chunks and then running LaTeX, which means that almost all figures, numbers, and results were generated while producing the PDF from the sources.

Companion to Psychiatric Studies E-Book

Companion to Psychiatric Studies E-Book
A Book

by Eve C Johnstone,David Cunningham Owens,Stephen M Lawrie

  • Publisher : Elsevier Health Sciences
  • Release : 2010-07-26
  • Pages : 864
  • ISBN : 1455725285
  • Language : En, Es, Fr & De
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* 2011 BMA Book Awards - Highly Commended in Psychiatry * A new edition of a classic textbook now published for the first time with colour. Covering the entire subject area [both basic sciences and clinical practice] in an easily accessible manner, the book is ideal for psychiatry trainees, especially candidates for postgraduate psychiatry exams, and qualified psychiatrists. New edition of a classic text with a strongly evidenced-based approach to both the basic sciences and clinical psychiatry Contains useful summary boxes to allow rapid access to complex information Comprehensive and authoritative resource written by contributors to ensure complete accuracy and currency of information Logical and accessible writing style gives ready access to key information Ideal for MRCPsych candidates and qualified psychiatrists Expanded section on psychology – including social psychology – to reflect the latest MRCPych examination format Discussion of capacity and its relationship to new legislation Text updated in full to reflect the new Mental Health Acts Relevant chapters now include discussion of core competencies and the practical skills required for the MRCPsych examination Includes a section on the wider role of the psychiatrist – including teaching and supervision, lifelong learning, and working as part of a multidisciplinary team (including dealing with conflict, discipline and complaints) Includes new chapter on transcultural aspects of psychiatry Enhanced discussion of the use of the best current management options, both pharmacological and psychotherapeutic, the latter including CBT (including its use in the treatment of psychosis) and group, couple and family therapy.

Functional Neuroimaging

Functional Neuroimaging
Technical Foundations

by Robert W. Thatcher,M. Hallett,T. Zeffiro,E. Roy John

  • Publisher : Unknown Publisher
  • Release : 1994
  • Pages : 303
  • ISBN : 9876543210XXX
  • Language : En, Es, Fr & De
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The 1990s have been designated by congress and the president as the decade of the brain, in part due to recognition of the expansion of knowledge and technology in the realm of neuroscience. Functional neuroimaging encompasses the technique of electrophysiology (EEG), magnetoecephalography (MEG), magnetic resonance imaging (MRI), and positron emission tomography (PET). Through these techniques, high resolution, 3 dimensional anatomical information can be obtained ofthe brain and it's functioning in normal and diseases states. Neuroscientists everywhere use neuroimaging in research, and these techniques are also used regularly by clinicians, and increasingly by biopsychologists. Given the increase in the number of techniques, and their diversity of applications, there is a need for a comprehensive volume to address both the technology and function of their use. Key Features * Addresses the technical problems of image registration * Compares different approaches to inter-subject and intra-subject analysis * Explores the synergestic advantages of multivolume integration * Divided into four sections devoted to relevant, timely issues

A Distribution-Free Theory of Nonparametric Regression

A Distribution-Free Theory of Nonparametric Regression
A Book

by László Györfi,Michael Kohler,Adam Krzyzak,Harro Walk

  • Publisher : Springer Science & Business Media
  • Release : 2006-04-18
  • Pages : 650
  • ISBN : 0387224424
  • Language : En, Es, Fr & De
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This book provides a systematic in-depth analysis of nonparametric regression with random design. It covers almost all known estimates. The emphasis is on distribution-free properties of the estimates.

Testing Statistical Assumptions in Research

Testing Statistical Assumptions in Research
A Book

by J. P. Verma,Abdel-Salam G. Abdel-Salam

  • Publisher : John Wiley & Sons
  • Release : 2019-03-04
  • Pages : 224
  • ISBN : 1119528402
  • Language : En, Es, Fr & De
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Comprehensively teaches the basics of testing statistical assumptions in research and the importance in doing so This book facilitates researchers in checking the assumptions of statistical tests used in their research by focusing on the importance of checking assumptions in using statistical methods, showing them how to check assumptions, and explaining what to do if assumptions are not met. Testing Statistical Assumptions in Research discusses the concepts of hypothesis testing and statistical errors in detail, as well as the concepts of power, sample size, and effect size. It introduces SPSS functionality and shows how to segregate data, draw random samples, file split, and create variables automatically. It then goes on to cover different assumptions required in survey studies, and the importance of designing surveys in reporting the efficient findings. The book provides various parametric tests and the related assumptions and shows the procedures for testing these assumptions using SPSS software. To motivate readers to use assumptions, it includes many situations where violation of assumptions affects the findings. Assumptions required for different non-parametric tests such as Chi-square, Mann-Whitney, Kruskal Wallis, and Wilcoxon signed-rank test are also discussed. Finally, it looks at assumptions in non-parametric correlations, such as bi-serial correlation, tetrachoric correlation, and phi coefficient. An excellent reference for graduate students and research scholars of any discipline in testing assumptions of statistical tests before using them in their research study Shows readers the adverse effect of violating the assumptions on findings by means of various illustrations Describes different assumptions associated with different statistical tests commonly used by research scholars Contains examples using SPSS, which helps facilitate readers to understand the procedure involved in testing assumptions Looks at commonly used assumptions in statistical tests, such as z, t and F tests, ANOVA, correlation, and regression analysis Testing Statistical Assumptions in Research is a valuable resource for graduate students of any discipline who write thesis or dissertation for empirical studies in their course works, as well as for data analysts.

EEG - fMRI

EEG - fMRI
Physiological Basis, Technique, and Applications

by Christoph Mulert,Louis Lemieux

  • Publisher : Springer Science & Business Media
  • Release : 2009-10-29
  • Pages : 539
  • ISBN : 9783540879190
  • Language : En, Es, Fr & De
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Functional magnetic resonance imaging (fMRI) and Electronecephalography (EEG) are very important and complementary modalities since fMRI offers high spatial resolution and EEG is a direct measurement of neuronal activity with high temporal resolution. Interest in the integration of both types of data is growing rapidly as it promises to provide important new insights into human brain activity as it has already done so in the field of epilepsy. The availability of good quality instrumentation capable of providing interference-free data in both modalities means that electrophysiological and haemodynamic characteristics of individual brain events can be captured for the first time. Consequently, it seems certain that the integration of fMRI and EEG will play an increasing role in neuroscience and of the clinical study of brain disorders such as epilepsy. The proposed book will discuss in detail the physiological principles, practical aspects of measurement, artefact reduction and analysis and also applications of the integration of fMRI and EEG. All applications, which are mainly in the fields of sleep research, cognitive neuroscience and clinical use in neurology and psychiatry will be reviewed.

A Modern Introduction to Probability and Statistics

A Modern Introduction to Probability and Statistics
Understanding Why and How

by F.M. Dekking,C. Kraaikamp,H.P. Lopuhaä,L.E. Meester

  • Publisher : Springer Science & Business Media
  • Release : 2006-03-30
  • Pages : 488
  • ISBN : 1846281687
  • Language : En, Es, Fr & De
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Suitable for self study Use real examples and real data sets that will be familiar to the audience Introduction to the bootstrap is included – this is a modern method missing in many other books

The Elements of Statistical Learning

The Elements of Statistical Learning
Data Mining, Inference, and Prediction

by Trevor Hastie,Robert Tibshirani,Jerome Friedman

  • Publisher : Springer Science & Business Media
  • Release : 2013-11-11
  • Pages : 536
  • ISBN : 0387216065
  • Language : En, Es, Fr & De
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During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.

The R Book

The R Book
A Book

by Michael J. Crawley

  • Publisher : John Wiley & Sons
  • Release : 2007-06-13
  • Pages : 950
  • ISBN : 9780470515068
  • Language : En, Es, Fr & De
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The high-level language of R is recognized as one of the most powerful and flexible statistical software environments, and is rapidly becoming the standard setting for quantitative analysis, statistics and graphics. R provides free access to unrivalled coverage and cutting-edge applications, enabling the user to apply numerous statistical methods ranging from simple regression to time series or multivariate analysis. Building on the success of the author’s bestselling Statistics: An Introduction using R, The R Book is packed with worked examples, providing an all inclusive guide to R, ideal for novice and more accomplished users alike. The book assumes no background in statistics or computing and introduces the advantages of the R environment, detailing its applications in a wide range of disciplines. Provides the first comprehensive reference manual for the R language, including practical guidance and full coverage of the graphics facilities. Introduces all the statistical models covered by R, beginning with simple classical tests such as chi-square and t-test. Proceeds to examine more advance methods, from regression and analysis of variance, through to generalized linear models, generalized mixed models, time series, spatial statistics, multivariate statistics and much more. The R Book is aimed at undergraduates, postgraduates and professionals in science, engineering and medicine. It is also ideal for students and professionals in statistics, economics, geography and the social sciences.

Introduction to Empirical Processes and Semiparametric Inference

Introduction to Empirical Processes and Semiparametric Inference
A Book

by Michael R. Kosorok

  • Publisher : Springer Science & Business Media
  • Release : 2007-12-29
  • Pages : 483
  • ISBN : 9780387749785
  • Language : En, Es, Fr & De
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Kosorok’s brilliant text provides a self-contained introduction to empirical processes and semiparametric inference. These powerful research techniques are surprisingly useful for developing methods of statistical inference for complex models and in understanding the properties of such methods. This is an authoritative text that covers all the bases, and also a friendly and gradual introduction to the area. The book can be used as research reference and textbook.

Statistical Inference

Statistical Inference
The Minimum Distance Approach

by Ayanendranath Basu,Hiroyuki Shioya,Chanseok Park

  • Publisher : CRC Press
  • Release : 2011-06-22
  • Pages : 429
  • ISBN : 1420099663
  • Language : En, Es, Fr & De
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In many ways, estimation by an appropriate minimum distance method is one of the most natural ideas in statistics. However, there are many different ways of constructing an appropriate distance between the data and the model: the scope of study referred to by "Minimum Distance Estimation" is literally huge. Filling a statistical resource gap, Statistical Inference: The Minimum Distance Approach comprehensively overviews developments in density-based minimum distance inference for independently and identically distributed data. Extensions to other more complex models are also discussed. Comprehensively covering the basics and applications of minimum distance inference, this book introduces and discusses: The estimation and hypothesis testing problems for both discrete and continuous models The robustness properties and the structural geometry of the minimum distance methods The inlier problem and its possible solutions, and the weighted likelihood estimation problem The extension of the minimum distance methodology in interdisciplinary areas, such as neural networks and fuzzy sets, as well as specialized models and problems, including semi-parametric problems, mixture models, grouped data problems, and survival analysis. Statistical Inference: The Minimum Distance Approach gives a thorough account of density-based minimum distance methods and their use in statistical inference. It covers statistical distances, density-based minimum distance methods, discrete and continuous models, asymptotic distributions, robustness, computational issues, residual adjustment functions, graphical descriptions of robustness, penalized and combined distances, weighted likelihood, and multinomial goodness-of-fit tests. This carefully crafted resource is useful to researchers and scientists within and outside the statistics arena.

Intelligent Systems Technologies and Applications 2016

Intelligent Systems Technologies and Applications 2016
A Book

by Juan Manuel Corchado Rodriguez,Sushmita Mitra,Sabu M. Thampi,El-Sayed El-Alfy

  • Publisher : Springer
  • Release : 2016-09-19
  • Pages : 1019
  • ISBN : 3319479520
  • Language : En, Es, Fr & De
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This book constitutes the thoroughly refereed proceedings of the second International Symposium on Intelligent Systems Technologies and Applications (ISTA’16), held on September 21–24, 2016 in Jaipur, India. The 80 revised papers presented were carefully reviewed and selected from 210 initial submissions and are organized in topical sections on image processing and artificial vision, computer networks and distributed systems, intelligent tools and techniques and applications using intelligent techniques.

Statistical Methods in Spatial Epidemiology

Statistical Methods in Spatial Epidemiology
A Book

by Andrew B. Lawson

  • Publisher : John Wiley & Sons
  • Release : 2013-07-08
  • Pages : 192
  • ISBN : 1118723171
  • Language : En, Es, Fr & De
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Spatial epidemiology is the description and analysis of the geographical distribution of disease. It is more important now than ever, with modern threats such as bio-terrorism making such analysis even more complex. This second edition of Statistical Methods in Spatial Epidemiology is updated and expanded to offer a complete coverage of the analysis and application of spatial statistical methods. The book is divided into two main sections: Part 1 introduces basic definitions and terminology, along with map construction and some basic models. This is expanded upon in Part II by applying this knowledge to the fundamental problems within spatial epidemiology, such as disease mapping, ecological analysis, disease clustering, bio-terrorism, space-time analysis, surveillance and infectious disease modelling. Provides a comprehensive overview of the main statistical methods used in spatial epidemiology. Updated to include a new emphasis on bio-terrorism and disease surveillance. Emphasizes the importance of space-time modelling and outlines the practical application of the method. Discusses the wide range of software available for analyzing spatial data, including WinBUGS, SaTScan and R, and features an accompanying website hosting related software. Contains numerous data sets, each representing a different approach to the analysis, and provides an insight into various modelling techniques. This text is primarily aimed at medical statisticians, researchers and practitioners from public health and epidemiology. It is also suitable for postgraduate students of statistics and epidemiology, as well professionals working in government agencies.

The Geometry of Random Fields

The Geometry of Random Fields
A Book

by Robert J. Adler

  • Publisher : SIAM
  • Release : 2010-01-28
  • Pages : 184
  • ISBN : 0898716934
  • Language : En, Es, Fr & De
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An important treatment of the geometric properties of sets generated by random fields, including a comprehensive treatment of the mathematical basics of random fields in general. It is a standard reference for all researchers with an interest in random fields, whether they be theoreticians or come from applied areas.