Spatio Temporal Statistics With R

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Spatio-Temporal Statistics with R

Christopher K. Wikle,Andrew Zammit-Mangion,Noel Cressie
Spatio Temporal Statistics with R Book PDF

Author : Christopher K. Wikle,Andrew Zammit-Mangion,Noel Cressie
Publisher : CRC Press
Page : 380 pages
File Size : 45,5 Mb
Release : 2019-02-18
Category : Mathematics
ISBN : 9780429649783

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Spatio-Temporal Statistics with R by Christopher K. Wikle,Andrew Zammit-Mangion,Noel Cressie Pdf

The world is becoming increasingly complex, with larger quantities of data available to be analyzed. It so happens that much of these "big data" that are available are spatio-temporal in nature, meaning that they can be indexed by their spatial locations and time stamps. Spatio-Temporal Statistics with R provides an accessible introduction to statistical analysis of spatio-temporal data, with hands-on applications of the statistical methods using R Labs found at the end of each chapter. The book: Gives a step-by-step approach to analyzing spatio-temporal data, starting with visualization, then statistical modelling, with an emphasis on hierarchical statistical models and basis function expansions, and finishing with model evaluation Provides a gradual entry to the methodological aspects of spatio-temporal statistics Provides broad coverage of using R as well as "R Tips" throughout. Features detailed examples and applications in end-of-chapter Labs Features "Technical Notes" throughout to provide additional technical detail where relevant Supplemented by a website featuring the associated R package, data, reviews, errata, a discussion forum, and more The book fills a void in the literature and available software, providing a bridge for students and researchers alike who wish to learn the basics of spatio-temporal statistics. It is written in an informal style and functions as a down-to-earth introduction to the subject. Any reader familiar with calculus-based probability and statistics, and who is comfortable with basic matrix-algebra representations of statistical models, would find this book easy to follow. The goal is to give as many people as possible the tools and confidence to analyze spatio-temporal data.

Statistics for Spatio-Temporal Data

Noel Cressie,Christopher K. Wikle
Statistics for Spatio Temporal Data Book PDF

Author : Noel Cressie,Christopher K. Wikle
Publisher : John Wiley & Sons
Page : 624 pages
File Size : 48,6 Mb
Release : 2015-11-02
Category : Mathematics
ISBN : 9781119243045

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Statistics for Spatio-Temporal Data by Noel Cressie,Christopher K. Wikle Pdf

Winner of the 2013 DeGroot Prize. A state-of-the-art presentation of spatio-temporal processes,bridging classic ideas with modern hierarchical statisticalmodeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winnersof the 2011 PROSE Award in the Mathematics category, for thebook “Statistics for Spatio-Temporal Data” (2011),published by John Wiley and Sons. (The PROSE awards, forProfessional and Scholarly Excellence, are given by the Associationof American Publishers, the national trade association of the USbook publishing industry.) Statistics for Spatio-Temporal Data has now beenreprinted with small corrections to the text andthe bibliography. The overall content and pagination of thenew printing remains the same; the difference comes inthe form of corrections to typographical errors, editing ofincomplete and missing references, and some updated spatio-temporalinterpretations. From understanding environmental processes and climate trends todeveloping new technologies for mapping public-health data and thespread of invasive-species, there is a high demand for statisticalanalyses of data that take spatial, temporal, and spatio-temporalinformation into account. Statistics for Spatio-TemporalData presents a systematic approach to key quantitativetechniques that incorporate the latest advances in statisticalcomputing as well as hierarchical, particularly Bayesian,statistical modeling, with an emphasis on dynamical spatio-temporalmodels. Cressie and Wikle supply a unique presentation thatincorporates ideas from the areas of time series and spatialstatistics as well as stochastic processes. Beginning with separatetreatments of temporal data and spatial data, the book combinesthese concepts to discuss spatio-temporal statistical methods forunderstanding complex processes. Topics of coverage include: Exploratory methods for spatio-temporal data, includingvisualization, spectral analysis, empirical orthogonal functionanalysis, and LISAs Spatio-temporal covariance functions, spatio-temporal kriging,and time series of spatial processes Development of hierarchical dynamical spatio-temporal models(DSTMs), with discussion of linear and nonlinear DSTMs andcomputational algorithms for their implementation Quantifying and exploring spatio-temporal variability inscientific applications, including case studies based on real-worldenvironmental data Throughout the book, interesting applications demonstrate therelevance of the presented concepts. Vivid, full-color graphicsemphasize the visual nature of the topic, and a related FTP sitecontains supplementary material. Statistics for Spatio-TemporalData is an excellent book for a graduate-level course onspatio-temporal statistics. It is also a valuable reference forresearchers and practitioners in the fields of applied mathematics,engineering, and the environmental and health sciences.

Bayesian Modeling of Spatio-Temporal Data with R

Sujit Sahu
Bayesian Modeling of Spatio Temporal Data with R Book PDF

Author : Sujit Sahu
Publisher : CRC Press
Page : 385 pages
File Size : 52,7 Mb
Release : 2022-02-23
Category : Mathematics
ISBN : 9781000543698

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Bayesian Modeling of Spatio-Temporal Data with R by Sujit Sahu Pdf

Applied sciences, both physical and social, such as atmospheric, biological, climate, demographic, economic, ecological, environmental, oceanic and political, routinely gather large volumes of spatial and spatio-temporal data in order to make wide ranging inference and prediction. Ideally such inferential tasks should be approached through modelling, which aids in estimation of uncertainties in all conclusions drawn from such data. Unified Bayesian modelling, implemented through user friendly software packages, provides a crucial key to unlocking the full power of these methods for solving challenging practical problems. Key features of the book: • Accessible detailed discussion of a majority of all aspects of Bayesian methods and computations with worked examples, numerical illustrations and exercises • A spatial statistics jargon buster chapter that enables the reader to build up a vocabulary without getting clouded in modeling and technicalities • Computation and modeling illustrations are provided with the help of the dedicated R package bmstdr, allowing the reader to use well-known packages and platforms, such as rstan, INLA, spBayes, spTimer, spTDyn, CARBayes, CARBayesST, etc • Included are R code notes detailing the algorithms used to produce all the tables and figures, with data and code available via an online supplement • Two dedicated chapters discuss practical examples of spatio-temporal modeling of point referenced and areal unit data • Throughout, the emphasis has been on validating models by splitting data into test and training sets following on the philosophy of machine learning and data science This book is designed to make spatio-temporal modeling and analysis accessible and understandable to a wide audience of students and researchers, from mathematicians and statisticians to practitioners in the applied sciences. It presents most of the modeling with the help of R commands written in a purposefully developed R package to facilitate spatio-temporal modeling. It does not compromise on rigour, as it presents the underlying theories of Bayesian inference and computation in standalone chapters, which would be appeal those interested in the theoretical details. By avoiding hard core mathematics and calculus, this book aims to be a bridge that removes the statistical knowledge gap from among the applied scientists.

Applied Spatial Data Analysis with R

Roger S. Bivand,Edzer Pebesma,Virgilio Gómez-Rubio
Applied Spatial Data Analysis with R Book PDF

Author : Roger S. Bivand,Edzer Pebesma,Virgilio Gómez-Rubio
Publisher : Springer Science & Business Media
Page : 414 pages
File Size : 54,7 Mb
Release : 2013-06-21
Category : Medical
ISBN : 9781461476184

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Applied Spatial Data Analysis with R by Roger S. Bivand,Edzer Pebesma,Virgilio Gómez-Rubio Pdf

Applied Spatial Data Analysis with R, second edition, is divided into two basic parts, the first presenting R packages, functions, classes and methods for handling spatial data. This part is of interest to users who need to access and visualise spatial data. Data import and export for many file formats for spatial data are covered in detail, as is the interface between R and the open source GRASS GIS and the handling of spatio-temporal data. The second part showcases more specialised kinds of spatial data analysis, including spatial point pattern analysis, interpolation and geostatistics, areal data analysis and disease mapping. The coverage of methods of spatial data analysis ranges from standard techniques to new developments, and the examples used are largely taken from the spatial statistics literature. All the examples can be run using R contributed packages available from the CRAN website, with code and additional data sets from the book's own website. Compared to the first edition, the second edition covers the more systematic approach towards handling spatial data in R, as well as a number of important and widely used CRAN packages that have appeared since the first edition. This book will be of interest to researchers who intend to use R to handle, visualise, and analyse spatial data. It will also be of interest to spatial data analysts who do not use R, but who are interested in practical aspects of implementing software for spatial data analysis. It is a suitable companion book for introductory spatial statistics courses and for applied methods courses in a wide range of subjects using spatial data, including human and physical geography, geographical information science and geoinformatics, the environmental sciences, ecology, public health and disease control, economics, public administration and political science. The book has a website where complete code examples, data sets, and other support material may be found: http://www.asdar-book.org. The authors have taken part in writing and maintaining software for spatial data handling and analysis with R in concert since 2003.

Spatial and Spatio-temporal Bayesian Models with R - INLA

Marta Blangiardo,Michela Cameletti
Spatial and Spatio temporal Bayesian Models with R INLA Book PDF

Author : Marta Blangiardo,Michela Cameletti
Publisher : John Wiley & Sons
Page : 321 pages
File Size : 40,6 Mb
Release : 2015-06-02
Category : Mathematics
ISBN : 9781118326558

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Spatial and Spatio-temporal Bayesian Models with R - INLA by Marta Blangiardo,Michela Cameletti Pdf

Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio­-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations

Spatiotemporal Data Analysis

Gidon Eshel
Spatiotemporal Data Analysis Book PDF

Author : Gidon Eshel
Publisher : Princeton University Press
Page : 337 pages
File Size : 44,5 Mb
Release : 2012
Category : Mathematics
ISBN : 9780691128917

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Spatiotemporal Data Analysis by Gidon Eshel Pdf

How do we study the storm's mutation into a deadly twister? Avian flu cases are reported in China.

Geospatial Health Data

Paula Moraga
Geospatial Health Data Book PDF

Author : Paula Moraga
Publisher : CRC Press
Page : 217 pages
File Size : 45,7 Mb
Release : 2019-11-26
Category : Medical
ISBN : 9781000732153

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Geospatial Health Data by Paula Moraga Pdf

Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging

José-María Montero,Gema Fernández-Avilés,Jorge Mateu
Spatial and Spatio Temporal Geostatistical Modeling and Kriging Book PDF

Author : José-María Montero,Gema Fernández-Avilés,Jorge Mateu
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 52,6 Mb
Release : 2015-08-18
Category : Mathematics
ISBN : 9781118762431

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Spatial and Spatio-Temporal Geostatistical Modeling and Kriging by José-María Montero,Gema Fernández-Avilés,Jorge Mateu Pdf

Statistical Methods for Spatial and Spatio-Temporal Data Analysis provides a complete range of spatio-temporal covariance functions and discusses ways of constructing them. This book is a unified approach to modeling spatial and spatio-temporal data together with significant developments in statistical methodology with applications in R. This book includes: Methods for selecting valid covariance functions from the empirical counterparts that overcome the existing limitations of the traditional methods. The most innovative developments in the different steps of the kriging process. An up-to-date account of strategies for dealing with data evolving in space and time. An accompanying website featuring R code and examples

Using R for Bayesian Spatial and Spatio-Temporal Health Modeling

Andrew B. Lawson
Using R for Bayesian Spatial and Spatio Temporal Health Modeling Book PDF

Author : Andrew B. Lawson
Publisher : CRC Press
Page : 300 pages
File Size : 53,8 Mb
Release : 2021-04-28
Category : Mathematics
ISBN : 9781000376708

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Using R for Bayesian Spatial and Spatio-Temporal Health Modeling by Andrew B. Lawson Pdf

Progressively more and more attention has been paid to how location affects health outcomes. The area of disease mapping focusses on these problems, and the Bayesian paradigm has a major role to play in the understanding of the complex interplay of context and individual predisposition in such studies of disease. Using R for Bayesian Spatial and Spatio-Temporal Health Modeling provides a major resource for those interested in applying Bayesian methodology in small area health data studies. Features: Review of R graphics relevant to spatial health data Overview of Bayesian methods and Bayesian hierarchical modeling as applied to spatial data Bayesian Computation and goodness-of-fit Review of basic Bayesian disease mapping models Spatio-temporal modeling with MCMC and INLA Special topics include multivariate models, survival analysis, missing data, measurement error, variable selection, individual event modeling, and infectious disease modeling Software for fitting models based on BRugs, Nimble, CARBayes and INLA Provides code relevant to fitting all examples throughout the book at a supplementary website The book fills a void in the literature and available software, providing a crucial link for students and professionals alike to engage in the analysis of spatial and spatio-temporal health data from a Bayesian perspective using R. The book emphasizes the use of MCMC via Nimble, BRugs, and CARBAyes, but also includes INLA for comparative purposes. In addition, a wide range of packages useful in the analysis of geo-referenced spatial data are employed and code is provided. It will likely become a key reference for researchers and students from biostatistics, epidemiology, public health, and environmental science.

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Elias T. Krainski,Virgilio Gómez-Rubio,Haakon Bakka,Amanda Lenzi,Daniela Castro-Camilo,Daniel Simpson,Finn Lindgren,Håvard Rue
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA Book PDF

Author : Elias T. Krainski,Virgilio Gómez-Rubio,Haakon Bakka,Amanda Lenzi,Daniela Castro-Camilo,Daniel Simpson,Finn Lindgren,Håvard Rue
Publisher : CRC Press
Page : 284 pages
File Size : 48,8 Mb
Release : 2018-12-07
Category : Mathematics
ISBN : 9780429629853

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Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA by Elias T. Krainski,Virgilio Gómez-Rubio,Haakon Bakka,Amanda Lenzi,Daniela Castro-Camilo,Daniel Simpson,Finn Lindgren,Håvard Rue Pdf

Modeling spatial and spatio-temporal continuous processes is an important and challenging problem in spatial statistics. Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA describes in detail the stochastic partial differential equations (SPDE) approach for modeling continuous spatial processes with a Matérn covariance, which has been implemented using the integrated nested Laplace approximation (INLA) in the R-INLA package. Key concepts about modeling spatial processes and the SPDE approach are explained with examples using simulated data and real applications. This book has been authored by leading experts in spatial statistics, including the main developers of the INLA and SPDE methodologies and the R-INLA package. It also includes a wide range of applications: * Spatial and spatio-temporal models for continuous outcomes * Analysis of spatial and spatio-temporal point patterns * Coregionalization spatial and spatio-temporal models * Measurement error spatial models * Modeling preferential sampling * Spatial and spatio-temporal models with physical barriers * Survival analysis with spatial effects * Dynamic space-time regression * Spatial and spatio-temporal models for extremes * Hurdle models with spatial effects * Penalized Complexity priors for spatial models All the examples in the book are fully reproducible. Further information about this book, as well as the R code and datasets used, is available from the book website at http://www.r-inla.org/spde-book. The tools described in this book will be useful to researchers in many fields such as biostatistics, spatial statistics, environmental sciences, epidemiology, ecology and others. Graduate and Ph.D. students will also find this book and associated files a valuable resource to learn INLA and the SPDE approach for spatial modeling.

Spatio-Temporal Methods in Environmental Epidemiology

Gavin Shaddick,James V. Zidek
Spatio Temporal Methods in Environmental Epidemiology Book PDF

Author : Gavin Shaddick,James V. Zidek
Publisher : CRC Press
Page : 395 pages
File Size : 41,8 Mb
Release : 2015-06-17
Category : Mathematics
ISBN : 9781482237047

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Spatio-Temporal Methods in Environmental Epidemiology by Gavin Shaddick,James V. Zidek Pdf

Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological Studies Spatio-Temporal Methods in Environmental Epidemiology is the first book of its kind to specifically address the interface between environmental epidemiology and spatio-temporal modeling. In response to the growing need for collaboration between statisticians and environmental epidemiologists, the book links recent developments in spatio-temporal methodology with epidemiological applications. Drawing on real-life problems, it provides the necessary tools to exploit advances in methodology when assessing the health risks associated with environmental hazards. The book’s clear guidelines enable the implementation of the methodology and estimation of risks in practice. Designed for graduate students in both epidemiology and statistics, the text covers a wide range of topics, from an introduction to epidemiological principles and the foundations of spatio-temporal modeling to new research directions. It describes traditional and Bayesian approaches and presents the theory of spatial, temporal, and spatio-temporal modeling in the context of its application to environmental epidemiology. The text includes practical examples together with embedded R code, details of specific R packages, and the use of other software, such as WinBUGS/OpenBUGS and integrated nested Laplace approximations (INLA). A supplementary website provides additional code, data, examples, exercises, lab projects, and more. Representing a major new direction in environmental epidemiology, this book—in full color throughout—underscores the increasing need to consider dependencies in both space and time when modeling epidemiological data. Students will learn how to identify and model patterns in spatio-temporal data as well as exploit dependencies over space and time to reduce bias and inefficiency.

Regression Modelling wih Spatial and Spatial-Temporal Data

Robert P. Haining,Guangquan Li
Regression Modelling wih Spatial and Spatial Temporal Data Book PDF

Author : Robert P. Haining,Guangquan Li
Publisher : CRC Press
Page : 527 pages
File Size : 49,5 Mb
Release : 2020-01-27
Category : Mathematics
ISBN : 9780429529108

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Regression Modelling wih Spatial and Spatial-Temporal Data by Robert P. Haining,Guangquan Li Pdf

Modelling Spatial and Spatial-Temporal Data: A Bayesian Approach is aimed at statisticians and quantitative social, economic and public health students and researchers who work with spatial and spatial-temporal data. It assumes a grounding in statistical theory up to the standard linear regression model. The book compares both hierarchical and spatial econometric modelling, providing both a reference and a teaching text with exercises in each chapter. The book provides a fully Bayesian, self-contained, treatment of the underlying statistical theory, with chapters dedicated to substantive applications. The book includes WinBUGS code and R code and all datasets are available online. Part I covers fundamental issues arising when modelling spatial and spatial-temporal data. Part II focuses on modelling cross-sectional spatial data and begins by describing exploratory methods that help guide the modelling process. There are then two theoretical chapters on Bayesian models and a chapter of applications. Two chapters follow on spatial econometric modelling, one describing different models, the other substantive applications. Part III discusses modelling spatial-temporal data, first introducing models for time series data. Exploratory methods for detecting different types of space-time interaction are presented followed by two chapters on the theory of space-time separable (without space-time interaction) and inseparable (with space-time interaction) models. An applications chapter includes: the evaluation of a policy intervention; analysing the temporal dynamics of crime hotspots; chronic disease surveillance; and testing for evidence of spatial spillovers in the spread of an infectious disease. A final chapter suggests some future directions and challenges.

An Introduction to R for Spatial Analysis and Mapping

Chris Brunsdon,Lex Comber
An Introduction to R for Spatial Analysis and Mapping Book PDF

Author : Chris Brunsdon,Lex Comber
Publisher : SAGE
Page : 475 pages
File Size : 46,8 Mb
Release : 2014-04-30
Category : Social Science
ISBN : 9781473911192

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An Introduction to R for Spatial Analysis and Mapping by Chris Brunsdon,Lex Comber Pdf

"In an age of big data, data journalism and with a wealth of quantitative information around us, it is not enough for students to be taught only 100 year old statistical methods using ′out of the box′ software. They need to have 21st-century analytical skills too. This is an excellent and student-friendly text from two of the world leaders in the teaching and development of spatial analysis. It shows clearly why the open source software R is not just an alternative to commercial GIS, it may actually be the better choice for mapping, analysis and for replicable research. Providing practical tips as well as fully working code, this is a practical ′how to′ guide ideal for undergraduates as well as those using R for the first time. It will be required reading on my own courses." - Richard Harris, Professor of Quantitative Social Science, University of Bristol R is a powerful open source computing tool that supports geographical analysis and mapping for the many geography and ‘non-geography’ students and researchers interested in spatial analysis and mapping. This book provides an introduction to the use of R for spatial statistical analysis, geocomputation and the analysis of geographical information for researchers collecting and using data with location attached, largely through increased GPS functionality. Brunsdon and Comber take readers from ‘zero to hero’ in spatial analysis and mapping through functions they have developed and compiled into R packages. This enables practical R applications in GIS, spatial analyses, spatial statistics, mapping, and web-scraping. Each chapter includes: Example data and commands for exploring it Scripts and coding to exemplify specific functionality Advice for developing greater understanding - through functions such as locator(), View(), and alternative coding to achieve the same ends Self-contained exercises for students to work through Embedded code within the descriptive text. This is a definitive ′how to′ that takes students - of any discipline - from coding to actual applications and uses of R.

Spatial Analysis with R

Tonny J. Oyana
Spatial Analysis with R Book PDF

Author : Tonny J. Oyana
Publisher : CRC Press
Page : 281 pages
File Size : 51,9 Mb
Release : 2020-08-31
Category : Mathematics
ISBN : 9781000173475

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Spatial Analysis with R by Tonny J. Oyana Pdf

In the five years since the publication of the first edition of Spatial Analysis: Statistics, Visualization, and Computational Methods, many new developments have taken shape regarding the implementation of new tools and methods for spatial analysis with R. The use and growth of artificial intelligence, machine learning and deep learning algorithms with a spatial perspective, and the interdisciplinary use of spatial analysis are all covered in this second edition along with traditional statistical methods and algorithms to provide a concept-based problem-solving learning approach to mastering practical spatial analysis. Spatial Analysis with R: Statistics, Visualization, and Computational Methods, Second Edition provides a balance between concepts and practicums of spatial statistics with a comprehensive coverage of the most important approaches to understand spatial data, analyze spatial relationships and patterns, and predict spatial processes. New in the Second Edition: Includes new practical exercises and worked-out examples using R Presents a wide range of hands-on spatial analysis worktables and lab exercises All chapters are revised and include new illustrations of different concepts using data from environmental and social sciences Expanded material on spatiotemporal methods, visual analytics methods, data science, and computational methods Explains big data, data management, and data mining This second edition of an established textbook, with new datasets, insights, excellent illustrations, and numerous examples with R, is perfect for senior undergraduate and first-year graduate students in geography and the geosciences.

Statistics for Spatial Data

Noel Cressie
Statistics for Spatial Data Book PDF

Author : Noel Cressie
Publisher : John Wiley & Sons
Page : 931 pages
File Size : 54,5 Mb
Release : 2015-03-18
Category : Mathematics
ISBN : 9781119115182

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Statistics for Spatial Data by Noel Cressie Pdf

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.