A Casebook For Spatial Statistical Data Analysis


A Casebook For Spatial Statistical Data Analysis
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A Casebook For Spatial Statistical Data Analysis


A Casebook For Spatial Statistical Data Analysis
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Author :
language : en
Publisher: Oxford University Press
Release Date : 1999

A Casebook For Spatial Statistical Data Analysis written by and has been published by Oxford University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.


This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallels between geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.



A Casebook For Spatial Statistical Data Analysis


A Casebook For Spatial Statistical Data Analysis
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Author : Daniel A. Griffith
language : en
Publisher:
Release Date : 2023

A Casebook For Spatial Statistical Data Analysis written by Daniel A. Griffith and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with Geography categories.




Spatial Statistical Data Analysis For Gis Users


Spatial Statistical Data Analysis For Gis Users
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Author : K. Krivoruchko
language : en
Publisher:
Release Date : 2011

Spatial Statistical Data Analysis For Gis Users written by K. Krivoruchko and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with categories.




Statistical Methods For Spatial Data Analysis


Statistical Methods For Spatial Data Analysis
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Author : Oliver Schabenberger
language : en
Publisher: CRC Press
Release Date : 2017-01-27

Statistical Methods For Spatial Data Analysis written by Oliver Schabenberger and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-01-27 with Mathematics categories.


Understanding spatial statistics requires tools from applied and mathematical statistics, linear model theory, regression, time series, and stochastic processes. It also requires a mindset that focuses on the unique characteristics of spatial data and the development of specialized analytical tools designed explicitly for spatial data analysis. Statistical Methods for Spatial Data Analysis answers the demand for a text that incorporates all of these factors by presenting a balanced exposition that explores both the theoretical foundations of the field of spatial statistics as well as practical methods for the analysis of spatial data. This book is a comprehensive and illustrative treatment of basic statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. It introduces essential tools and approaches including: measures of autocorrelation and their role in data analysis; the background and theoretical framework supporting random fields; the analysis of mapped spatial point patterns; estimation and modeling of the covariance function and semivariogram; a comprehensive treatment of spatial analysis in the spectral domain; and spatial prediction and kriging. The volume also delivers a thorough analysis of spatial regression, providing a detailed development of linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data. It succinctly discusses Bayesian hierarchical models and concludes with reviews on simulating random fields, non-stationary covariance, and spatio-temporal processes. Additional material on the CRC Press website supplements the content of this book. The site provides data sets used as examples in the text, software code that can be used to implement many of the principal methods described and illustrated, and updates to the text itself.



Practical Handbook Of Spatial Statistics


Practical Handbook Of Spatial Statistics
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Author : Sandra Arlinghaus
language : en
Publisher: CRC Press
Release Date : 2020-08-26

Practical Handbook Of Spatial Statistics written by Sandra Arlinghaus and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-26 with Mathematics categories.


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.



Spatial Data Analysis


Spatial Data Analysis
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Author : Robert P. Haining
language : en
Publisher: Cambridge University Press
Release Date : 2003-04-17

Spatial Data Analysis written by Robert P. Haining and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003-04-17 with Business & Economics categories.


Spatial Data Analysis: Theory and Practice, first published in 2003, provides a broad ranging treatment of the field of spatial data analysis. It begins with an overview of spatial data analysis and the importance of location (place, context and space) in scientific and policy related research. Covering fundamental problems concerning how attributes in geographical space are represented to the latest methods of exploratory spatial data analysis and spatial modeling, it is designed to take the reader through the key areas that underpin the analysis of spatial data, providing a platform from which to view and critically appreciate many of the key areas of the field. Parts of the text are accessible to undergraduate and master's level students, but it also contains sufficient challenging material that it will be of interest to geographers, social and economic scientists, environmental scientists and statisticians, whose research takes them into the area of spatial analysis.



Applied Spatial Data Analysis With R


Applied Spatial Data Analysis With R
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Author : Roger S. Bivand
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-21

Applied Spatial Data Analysis With R written by Roger S. Bivand and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-21 with Medical categories.


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 Statistics


Spatial Statistics
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Author : Brian D. Ripley
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-25

Spatial Statistics written by Brian D. Ripley and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-25 with Mathematics categories.


The Wiley-Interscience Paperback Series consists of selected booksthat have been made more accessible to consumers in an effort toincrease global appeal and general circulation. With these newunabridged softcover volumes, Wiley hopes to extend the lives ofthese works by making them available to future generations ofstatisticians, mathematicians, and scientists. "Books such as this that bring together, clarify, and summarizerecent research can lead to a great increase of interest in thearea. . . . a major achievement in describing many aspects ofspatial data and discussing, with examples, different methods ofanalysis." –Royal Statistical Society "Dr. Ripley’s book is an excellent survey of the spatialstatistical methodology. It is very well illustrated with examples[that] give a clear view of the wide scope of the subject, the wayin which techniques often have to be tailored to particularapplications, and the different sorts of spatial data thatarise." –The Bulletin of the London Mathematics Society Spatial Statistics provides a comprehensive guide to theanalysis of spatial data. Each chapter covers a particular dataformat and the associated class of problems, introducing theory,giving computational suggestions, and providing examples. Methodsare illustrated by computer-drawn figures. The book serves as anintroduction to this rapidly growing research area formathematicians and statisticians, and as a reference to newcomputer methods for researchers in ecology, geology, archaeology,and the earth sciences.



Advanced Spatial Statistics


Advanced Spatial Statistics
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Author : Daniel A. Griffith
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Advanced Spatial Statistics written by Daniel A. Griffith and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Business & Economics categories.


In recent years there has been a growing interest in and concern for the development of a sound spatial statistical body of theory. This work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g. , sociologists). It has led to the publication of a number of books, including Cliff and Ord's Spatial Processes (1981), Bartlett's The Statistical Analysis of Spatial Pattern (1975), Ripley's Spatial Statistics (1981), Paelinck and Klaassen's Spatial Economet~ics (1979), Ahuja and Schachter's Pattern Models (1983), and Upton and Fingleton's Spatial Data Analysis by Example (1985). The first of these books presents a useful introduction to the topic of spatial autocorrelation, focusing on autocorrelation indices and their sampling distributions. The second of these books is quite brief, but nevertheless furnishes an eloquent introduction to the rela tionship between spatial autoregressive and two-dimensional spectral models. Ripley's book virtually ignores autoregressive and trend surface modelling, and focuses almost solely on point pattern analysis. Paelinck and Klaassen's book closely follows an econometric textbook format, and as a result overlooks much of the important material necessary for successful spatial data analy sis. It almost exclusively addresses distance and gravity models, with some treatment of autoregressive modelling. Pattern Models supplements Cliff and Ord's book, which in combination provide a good introduction to spatial data analysis. Its basic limitation is a preoccupation with the geometry of planar patterns, and hence is very narrow in scope.



Spatial Statistical Methods For Geography


Spatial Statistical Methods For Geography
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Author : Peter A. Rogerson
language : en
Publisher: SAGE
Release Date : 2021-03-17

Spatial Statistical Methods For Geography written by Peter A. Rogerson and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-17 with Social Science categories.


This accessible new textbook offers a straightforward introduction to doing spatial statistics. Grounded in real world examples, it shows you how to extend traditional statistical methods for use with spatial data. The book assumes basic mathematical and statistics knowledge but also provides a handy refresher guide, so that you can develop your understanding and progress confidently. It also: · Equips you with the tools to both interpret and apply spatial statistical methods · Engages with the unique considerations that apply when working with geographic data · Helps you build your knowledge of key spatial statistical techniques, such as methods of geographic cluster detection.