spatial cluster modelling monographs on statistics and applied probability

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Robust Cluster Analysis And Variable Selection

Author : Gunter Ritter
ISBN : 9781439857960
Genre : Computers
File Size : 37. 82 MB
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Clustering remains a vibrant area of research in statistics. Although there are many books on this topic, there are relatively few that are well founded in the theoretical aspects. In Robust Cluster Analysis and Variable Selection, Gunter Ritter presents an overview of the theory and applications of probabilistic clustering and variable selection, synthesizing the key research results of the last 50 years. The author focuses on the robust clustering methods he found to be the most useful on simulated data and real-time applications. The book provides clear guidance for the varying needs of both applications, describing scenarios in which accuracy and speed are the primary goals. Robust Cluster Analysis and Variable Selection includes all of the important theoretical details, and covers the key probabilistic models, robustness issues, optimization algorithms, validation techniques, and variable selection methods. The book illustrates the different methods with simulated data and applies them to real-world data sets that can be easily downloaded from the web. This provides you with guidance in how to use clustering methods as well as applicable procedures and algorithms without having to understand their probabilistic fundamentals.

Spatial Cluster Modelling

Author : Andrew B. Lawson
ISBN : 9781420035414
Genre : Mathematics
File Size : 77. 42 MB
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Research has generated a number of advances in methods for spatial cluster modelling in recent years, particularly in the area of Bayesian cluster modelling. Along with these advances has come an explosion of interest in the potential applications of this work, especially in epidemiology and genome research. In one integrated volume, this book reviews the state-of-the-art in spatial clustering and spatial cluster modelling, bringing together research and applications previously scattered throughout the literature. It begins with an overview of the field, then presents a series of chapters that illuminate the nature and purpose of cluster modelling within different application areas, including astrophysics, epidemiology, ecology, and imaging. The focus then shifts to methods, with discussions on point and object process modelling, perfect sampling of cluster processes, partitioning in space and space-time, spatial and spatio-temporal process modelling, nonparametric methods for clustering, and spatio-temporal cluster modelling. Many figures, some in full color, complement the text, and a single section of references cited makes it easy to locate source material. Leading specialists in the field of cluster modelling authored each chapter, and an introduction by the editors to each chapter provides a cohesion not typically found in contributed works. Spatial Cluster Modelling thus offers a singular opportunity to explore this exciting new field, understand its techniques, and apply them in your own research.

Spatial Statistics And Computational Methods

Author : Jesper Møller
ISBN : 9780387218113
Genre : Mathematics
File Size : 71. 22 MB
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This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It introduces topics of current interest in spatial and computational statistics, which should be accessible to postgraduate students as well as to experienced statistical researchers.

Statistical Analysis Of Spatial And Spatio Temporal Point Patterns Third Edition

Author : Peter J. Diggle
ISBN : 9781466560246
Genre : Mathematics
File Size : 85. 32 MB
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Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data. Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences. This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author’s website.

Computational Science And Its Applications Iccsa 2008

Author : Osvaldo Gervasi
ISBN : 9783540698388
Genre : Computers
File Size : 21. 92 MB
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The two-volume set LNCS 5072 and 5073 constitutes the refereed proceedings of the International Conference on Computational Science and Its Applications, ICCSA 2008, held in Perugia, Italy, in June/July, 2008. The two volumes contain papers presenting a wealth of original research results in the field of computational science, from foundational issues in computer science and mathematics to advanced applications in virtually all sciences making use of computational techniques. The topics of the fully refereed papers are structured according to the five major conference themes: computational methods, algorithms and scientific applications, high performance technical computing and networks, advanced and emerging applications, geometric modelling, graphics and visualization, as well as information systems and information technologies. Moreover, submissions from more than 20 workshops and technical sessions in the areas, such as embedded systems, geographical analysis, computational geometry, computational geomatics, computer graphics, virtual reality, computer modeling, computer algebra, mobile communications, wireless networks, computational forensics, data storage, information security, web learning, software engineering, computational intelligence, digital security, biometrics, molecular structures, material design, ubiquitous computing, symbolic computations, web systems and intelligence, and e-education contribute to this publication.

Topics In Modelling Of Clustered Data

Author : Marc Aerts
ISBN : 9781420035889
Genre : Mathematics
File Size : 52. 25 MB
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Many methods for analyzing clustered data exist, all with advantages and limitations in particular applications. Compiled from the contributions of leading specialists in the field, Topics in Modelling of Clustered Data describes the tools and techniques for modelling the clustered data often encountered in medical, biological, environmental, and social science studies. It focuses on providing a comprehensive treatment of marginal, conditional, and random effects models using, among others, likelihood, pseudo-likelihood, and generalized estimating equations methods. The authors motivate and illustrate all aspects of these models in a variety of real applications. They discuss several variations and extensions, including individual-level covariates and combined continuous and discrete outcomes. Flexible modelling with fractional and local polynomials, omnibus lack-of-fit tests, robustification against misspecification, exact, and bootstrap inferential procedures all receive extensive treatment. The applications discussed center primarily, but not exclusively, on developmental toxicity, which leads naturally to discussion of other methodologies, including risk assessment and dose-response modelling. Clearly written, Topics in Modelling of Clustered Data offers a practical, easily accessible survey of important modelling issues. Overview models give structure to a multitude of approaches, figures help readers visualize model characteristics, and a generous use of examples illustrates all aspects of the modelling process.

Case Studies In Spatial Point Process Modeling

Author : Adrian Baddeley
ISBN : 9780387311449
Genre : Mathematics
File Size : 63. 61 MB
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Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples. Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies. From the reviews: "For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006

Medical Applications Of Finite Mixture Models

Author : Peter Schlattmann
ISBN : 9783540686514
Genre : Medical
File Size : 79. 93 MB
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Patients are not alike! This simple truth is often ignored in the analysis of me- cal data, since most of the time results are presented for the “average” patient. As a result, potential variability between patients is ignored when presenting, e.g., the results of a multiple linear regression model. In medicine there are more and more attempts to individualize therapy; thus, from the author’s point of view biostatis- cians should support these efforts. Therefore, one of the tasks of the statistician is to identify heterogeneity of patients and, if possible, to explain part of it with known explanatory covariates. Finite mixture models may be used to aid this purpose. This book tries to show that there are a large range of applications. They include the analysis of gene - pression data, pharmacokinetics, toxicology, and the determinants of beta-carotene plasma levels. Other examples include disease clustering, data from psychophysi- ogy, and meta-analysis of published studies. The book is intended as a resource for those interested in applying these methods.

Statistical Challenges In Modern Astronomy Iv

Author : Gutti Jogesh Babu
ISBN : 1583812407
Genre : Science
File Size : 23. 79 MB
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"This is the fourth in a series of international conferences for the vanguard of researchers in the cross-disciplinary field of astrostatistics. Both astronomical and statistical communities now recognize the wide array of fascinating methodological issues faced by the modern astronomer. Ranging from terabyte wide-field surveys to small-N samples, from cosmology to the search for Earth-like planets, astronomical research can no longer be pursued with a small toolbox of familiar statistical methods. Over thirty distinguished scholars from both fields presented invited talks and commentaries on leading problems in astrostatistics. The methodological challenges of inferring cosmological insights from the cosmic microwave background fluctuations, the distribution of galaxies in space, gravitational lensing, and galaxy structure wre describe in detail. Time series analysis is discussed in a variety of contexts: sparse Poisson data, multiply-periodic systems, gravitational wave detection, and most dramatically in the search for extrasolar planets. Here sophisticated Bayesian model selection with MCMC computations plays a critical role. Other topics covered include image processing, analysis of mega-datasets from large surveys, and small-N problems in both astronomy and particle physics. The volume ends with cross-disciplinary overviews and software tutorials. The book will be valuable to graduate students and researchers in both astronomy and statistics who seek insights into this promising avenue of cross-disciplinary research."--Publisher's website.

Gaussian Markov Random Fields

Author : Havard Rue
ISBN : 0203492021
Genre : Mathematics
File Size : 80. 77 MB
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Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studies and, online, a c-library for fast and exact simulation. With chapters contributed by leading researchers in the field, this volume is essential reading for statisticians working in spatial theory and its applications, as well as quantitative researchers in a wide range of science fields where spatial data analysis is important.

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