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Author: Carlo Gaetan Publisher: Springer Science & Business Media ISBN: 0387922571 Category : Mathematics Languages : en Pages : 308
Book Description
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI).
Author: Carlo Gaetan Publisher: Springer Science & Business Media ISBN: 0387922571 Category : Mathematics Languages : en Pages : 308
Book Description
Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI).
Author: Jean-Marc Zaninetti Publisher: Hermes Science Publications ISBN: 9782746212039 Category : Geographic information systems Languages : fr Pages : 320
Book Description
Cet ouvrage propose une synthèse des méthodes spécifiques de la statistique spatiale et permet d'analyser l'information géographique dans différents domaines d'études. Il est conçu dans une perspective interdisciplinaire, allant des sciences de l'environnement aux sciences sociales en associant la recherche fondamentale et la recherche appliquée. La statistique spatiale intéresse des disciplines aussi diverses que l'aménagement, l'archéologie, la criminologie, l'écologie, l'économie, l'épidémiologie, la géographie, la géologie, le géomarketing ou la météorologie auxquelles elle propose une méthode d'aide à la décision. Le développement de la géomatique a accru considérablement la demande de méthode. On observe actuellement une floraison de logiciels dédiés à l'analyse spatiale. Ce livre présente un certain nombre de logiciels libres employés pour réaliser les exemples originaux qui illustrent les différents chapitres
Author: Griffith, Daniel A. Publisher: Edward Elgar Publishing ISBN: 1800372825 Category : Social Science Languages : en Pages : 125
Book Description
This Advanced Introduction provides a critical review and discussion of research concerning spatial statistics, differentiating between it and spatial econometrics, to answer a set of core questions covering the geographic-tagging-of-data origins of the concept and its theoretical underpinnings, conceptual advances, and challenges for future scholarly work. It offers a vital tool for understanding spatial statistics and surveys how concerns about violating the independent observations assumption of statistical analysis developed into this discipline.
Author: Sandra Arlinghaus Publisher: CRC Press ISBN: 1000102017 Category : Mathematics Languages : en Pages : 324
Book Description
The guidance and special techniques provided in this handbook will allow you to understand and use complex spatial statistical techniques. You will learn how to apply proper spatial analysis techniques and why they are generally different from conventional statistical analyses. Clear and concise information on weighting, aggregation effects, sampling, spatial statistics and GIS, and visualization of spatial dependence is provided. Discussions on specific applications using actual data sets fill obvious gaps in the literature, and coverage of critical research frontiers allows readers to explore current areas of active research.
Author: Marc Moore Publisher: Springer Science & Business Media ISBN: 1461301475 Category : Mathematics Languages : en Pages : 296
Book Description
This volume contains presentations by eminent researchers: Statistical Inference for Spatial Processes; Image Analysis; Applications of Spatial Statistics in Earth, Environmental, and Health Sciences; and Statistics of Brain Mapping. They range from asymptotic considerations for spatial processes to practical considerations related to particular applications including important methodological aspects. Many contributions concern image analysis, mainly images related to brain mapping.
Author: Yongwan Chun Publisher: SAGE ISBN: 1446272117 Category : Reference Languages : en Pages : 201
Book Description
"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice" - Professor Tao Cheng, University College London Focusing specifically on spatial statistics and including components for ArcGIS, R, SAS and WinBUGS, this book illustrates the use of basic spatial statistics and geostatistics, as well as the spatial filtering techniques used in all relevant programs and software. It explains and demonstrates techniques in: spatial sampling spatial autocorrelation local statistics spatial interpolation in two-dimensions advanced topics including Bayesian methods, Monte Carlo simulation, error and uncertainty. It is a systematic overview of the fundamental spatial statistical methods used by applied researchers in geography, environmental science, health and epidemiology, population and demography, and planning. A companion website includes digital R code for implementing the analyses in specific chapters and relevant data sets to run the R codes.
Book Description
Les systèmes d'information géographique (SIG) caractérisent à la fois un modèle numérisé de l'espace géographique, mais aussi l'ensemble des outils de traitement de l'information associés. Combinant informations géographiques et statistiques, ils permettent un suivi cartographié et quantifié des dynamiques territoriales. La plupart des collectivités publiques ont aujourd'hui achevé l'acquisition et la structuration de ce type de données. Les bases résultantes sont mises à disposition du public et des praticiens, mais la richesse et la diversité des informations qu'elles proposent rendent leur exploitation complexe, dans la mesure où elles requièrent des connaissances développées en analyse spatiale. Cet ouvrage se propose de procurer au lecteur l'ensemble des outils nécessaires à la maîtrise et à l'exploitation de ces méthodes, notamment dans le cadre de la géostatistique appliquée aux phénomènes discrets et continus, de l'analyse du relief, de la formulation de requêtes spatiales, des aptitudes des réseaux (accessibilité et zones d'influence) et des objets zonaux (analyse multivariée associée à l'aide à la décision), de la dynamique spatiale ou de la propagation des incertitudes. Manuel sans équivalent, couvrant l'ensemble du domaine de l'exploitation des informations spatiales et de leur analyse dans une perspective d'aide à la décision. Très pédagogique : trois niveaux de lecture (bases, compréhension scientifique des phénomènes, méthodes opérationnelles), nombreuses questions de révision et suggestions de lecture en fin de chaque chapitre. Clair et didactique, cet ouvrage s'adresse à un large public d'étudiants en géosciences et en sciences de l'environnement, mais aussi de géographes et d'ingénieurs praticiens à la recherche d'un ouvrage de référence. [4e de couverture]
Author: Noel Cressie Publisher: John Wiley & Sons ISBN: 1119115183 Category : Mathematics Languages : en Pages : 931
Book Description
The Wiley Classics Library consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists. Spatial statistics — analyzing spatial data through statistical models — has proven exceptionally versatile, encompassing problems ranging from the microscopic to the astronomic. However, for the scientist and engineer faced only with scattered and uneven treatments of the subject in the scientific literature, learning how to make practical use of spatial statistics in day-to-day analytical work is very difficult. Designed exclusively for scientists eager to tap into the enormous potential of this analytical tool and upgrade their range of technical skills, Statistics for Spatial Data is a comprehensive, single-source guide to both the theory and applied aspects of spatial statistical methods. The hard-cover edition was hailed by Mathematical Reviews as an "excellent book which will become a basic reference." This paper-back edition of the 1993 edition, is designed to meet the many technological challenges facing the scientist and engineer. Concentrating on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, revealing how design, inference, and diagnostics are an outgrowth of that link. It then explores new methods to reveal just how spatial statistical models can be used to solve important problems in a host of areas in science and engineering. Discussion includes: Exploratory spatial data analysis Spectral theory for stationary processes Spatial scale Simulation methods for spatial processes Spatial bootstrapping Statistical image analysis and remote sensing Computational aspects of model fitting Application of models to disease mapping Designed to accommodate the practical needs of the professional, it features a unified and common notation for its subject as well as many detailed examples woven into the text, numerous illustrations (including graphs that illuminate the theory discussed) and over 1,000 references. Fully balancing theory with applications, Statistics for Spatial Data, Revised Edition is an exceptionally clear guide on making optimal use of one of the ascendant analytical tools of the decade, one that has begun to capture the imagination of professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology.
Author: Carlo Gaetan
Author: Carlo Gaetan
Author: Jean-Marc Zaninetti
Author: Griffith, Daniel A.
Author: 
Author: Jean-Pierre Bocquet-Appel
Author: Sandra Arlinghaus
Author: Marc Moore
Author: Yongwan Chun
Author: Régis Caloz
Author: Noel Cressie