Model Based Geostatistics

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Model Based Geostatistics

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Author : Peter Diggle
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-05-26

Model Based Geostatistics written by Peter Diggle 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 2007-05-26 with Science categories.

This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.

Model Based Geostatistics For Global Public Health

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Author : Peter J. Diggle
language : en
Publisher: CRC Press
Release Date : 2019-03-04

Model Based Geostatistics For Global Public Health written by Peter J. Diggle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-04 with Mathematics categories.

Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the authors describe and explain the pattern of spatial variation in a health outcome or exposure measurement of interest. Model-based geostatistics uses explicit probability models and established principles of statistical inference to address questions of this kind. Features: Presents state-of-the-art methods in model-based geostatistics. Discusses the application these methods some of the most challenging global public health problems including disease mapping, exposure mapping and environmental epidemiology. Describes exploratory methods for analysing geostatistical data, including: diagnostic checking of residuals standard linear and generalized linear models; variogram analysis; Gaussian process models and geostatistical design issues. Includes a range of more complex geostatistical problems where research is ongoing. All of the results in the book are reproducible using publicly available R code and data-sets, as well as a dedicated R package. This book has been written to be accessible not only to statisticians but also to students and researchers in the public health sciences. The Authors Peter Diggle is Distinguished University Professor of Statistics in the Faculty of Health and Medicine, Lancaster University. He also holds honorary positions at the Johns Hopkins University School of Public Health, Columbia University International Research Institute for Climate and Society, and Yale University School of Public Health. His research involves the development of statistical methods for analyzing spatial and longitudinal data and their applications in the biomedical and health sciences. Dr Emanuele Giorgi is a Lecturer in Biostatistics and member of the CHICAS research group at Lancaster University, where he formerly obtained a PhD in Statistics and Epidemiology in 2015. His research interests involve the development of novel geostatistical methods for disease mapping, with a special focus on malaria and other tropical diseases. In 2018, Dr Giorgi was awarded the Royal Statistical Society Research Prize "for outstanding published contribution at the interface of statistics and epidemiology." He is also the lead developer of PrevMap, an R package where all the methodology found in this book has been implemented.

Model Based Geostatistics For Global Public Health

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Author : Peter J. Diggle
language : en
Publisher: CRC Press
Release Date : 2019-03-04

Model Based Geostatistics For Global Public Health written by Peter J. Diggle and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-04 with Technology & Engineering categories.

Model-based Geostatistics for Global Public Health: Methods and Applications provides an introductory account of model-based geostatistics, its implementation in open-source software and its application in public health research. In the public health problems that are the focus of this book, the authors describe and explain the pattern of spatial variation in a health outcome or exposure measurement of interest. Model-based geostatistics uses explicit probability models and established principles of statistical inference to address questions of this kind. Features: Presents state-of-the-art methods in model-based geostatistics. Discusses the application these methods some of the most challenging global public health problems including disease mapping, exposure mapping and environmental epidemiology. Describes exploratory methods for analysing geostatistical data, including: diagnostic checking of residuals standard linear and generalized linear models; variogram analysis; Gaussian process models and geostatistical design issues. Includes a range of more complex geostatistical problems where research is ongoing. All of the results in the book are reproducible using publicly available R code and data-sets, as well as a dedicated R package. This book has been written to be accessible not only to statisticians but also to students and researchers in the public health sciences. The Authors Peter Diggle is Distinguished University Professor of Statistics in the Faculty of Health and Medicine, Lancaster University. He also holds honorary positions at the Johns Hopkins University School of Public Health, Columbia University International Research Institute for Climate and Society, and Yale University School of Public Health. His research involves the development of statistical methods for analyzing spatial and longitudinal data and their applications in the biomedical and health sciences. Dr Emanuele Giorgi is a Lecturer in Biostatistics and member of the CHICAS research group at Lancaster University, where he formerly obtained a PhD in Statistics and Epidemiology in 2015. His research interests involve the development of novel geostatistical methods for disease mapping, with a special focus on malaria and other tropical diseases. In 2018, Dr Giorgi was awarded the Royal Statistical Society Research Prize "for outstanding published contribution at the interface of statistics and epidemiology." He is also the lead developer of PrevMap, an R package where all the methodology found in this book has been implemented.

Model Based Geostatistics

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Author : Peter J. Diggle
language : en
Publisher:
Release Date : 2007

Model Based Geostatistics written by Peter J. Diggle and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with Geology categories.

This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.

Geoenv Vii Geostatistics For Environmental Applications

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Author : Peter M. Atkinson
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-03

Geoenv Vii Geostatistics For Environmental Applications written by Peter M. Atkinson 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 2010-07-03 with Science categories.

This volume brings together selected contributions from geoENV 2008, the 7th International Conference on Geostatistics for Environmental Applications, held in Southampton, UK. It presents the state-of-the-art in geostatistics for the environmental sciences.

Correlated Data Analysis Modeling Analytics And Applications

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Author : Peter X. -K. Song
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-30

Correlated Data Analysis Modeling Analytics And Applications written by Peter X. -K. Song 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 2007-06-30 with Mathematics categories.

This book covers recent developments in correlated data analysis. It utilizes the class of dispersion models as marginal components in the formulation of joint models for correlated data. This enables the book to cover a broader range of data types than the traditional generalized linear models. The reader is provided with a systematic treatment for the topic of estimating functions, and both generalized estimating equations (GEE) and quadratic inference functions (QIF) are studied as special cases. In addition to the discussions on marginal models and mixed-effects models, this book covers new topics on joint regression analysis based on Gaussian copulas.

Stochastic Modeling And Geostatistics

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Author : Timothy C. Coburn
language : en
Publisher: AAPG
Release Date : 2005-12-10

Stochastic Modeling And Geostatistics written by Timothy C. Coburn and has been published by AAPG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-12-10 with Petroleum categories.

Geoenv Iii Geostatistics For Environmental Applications

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Author : Pascal Monestiez
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Geoenv Iii Geostatistics For Environmental Applications written by Pascal Monestiez 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 Science categories.

This volume contains selected contributions from geoENV III - the Third European Conference on Geostatistics for Environmental Sciences, held in Avignon, France in November 2000. This third book of the geoENV series illustrates the new methodological developments in geostatistics, as applied to environmental sciences, which have occurred during the last two years. It also presents a wide variety of practical environmental applications which will be of interest to both researchers and practitioners. The book starts with two keynote papers on hydrogeology and on climatology and atmospheric pollution, followed by forty contributions. The content of this book is foremost practical. The editors have endeavored to compile a set of papers in which the readers could perceive how geostatistics is applied within environmental sciences. A few selected methodological and theoretical contributions are also included. The papers are organised in the following sections: Air Pollution / Climate; Environment; Health / Ecology; Hydrology; Methods; Soil Science / Site Remediation. presenting applications varying from delineation of hazardous areas, monitoring water quality, space-time modeling of sand beaches, areal rainfall estimation, air pollution monitoring, multivariate conditional simulation, soil texture analysis, fish abundance analysis, tree productivity index estimation, radionuclide migration analysis, wombling procedure, tracer tests modeling, direct sequential co-simulation to stochastic modeling of flow and transport. Audience: This publication will be of great interest and practical value to geostatisticians working both in academia and in industry.

Scale In Spatial Information And Analysis

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Author : Jingxiong Zhang
language : en
Publisher: CRC Press
Release Date : 2014-04-15

Scale In Spatial Information And Analysis written by Jingxiong Zhang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-15 with Mathematics categories.

Now ubiquitous in modern life, spatial data present great opportunities to transform many of the processes on which we base our everyday lives. However, not only do these data depend on the scale of measurement, but also handling these data (e.g., to make suitable maps) requires that we account for the scale of measurement explicitly. Scale in Spatial Information and Analysis describes the scales of measurement and scales of spatial variation that exist in the measured data. It provides you with a series of tools for handling spatial data while accounting for scale. The authors detail a systematic strategy for handling scale issues from geographic reality, through measurements, to resultant spatial data and their analyses. They also explore a process-pattern paradigm in approaching scale issues. This is well reflected, for example, in chapters dealing with terrain analysis, in which scale in terrain derivatives is described in relation to the processing involved in the derivation of specific terrain variables from elevation data, and area classes, which are viewed as driven by class-forming covariates. Lastly, this book provides coverage of some of the issues related to scale that are relatively under-represented in the literature, such as the effects of scale on information content in remotely sensed images, and the interaction between scale and uncertainty that is increasingly important for spatial information and analysis. By taking a rigorous, scientific approach to scale and its various meanings in relation to the geographic world, the book alleviates some of the frustration caused by dealing with issues of scale. While past research has led to an increasing number of journal articles and a few books dedicated to scale modeling and change of scale, this book helps you to develop coherent strategies for scale modeling, highlighting applicability for a variety of fields, from geomatic engineering and geoinformatics to environmental modeling.

Spatial Statistics For Data Science

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Author : Paula Moraga
language : en
Publisher: CRC Press
Release Date : 2023-12-08

Spatial Statistics For Data Science written by Paula Moraga and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-08 with Mathematics categories.

Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners. Key Features: Describes R packages for retrieval, manipulation, and visualization of spatial data Offers a comprehensive overview of spatial statistical methods including spatial autocorrelation, clustering, spatial interpolation, model-based geostatistics, and spatial point processes Provides detailed explanations on how to fit and interpret Bayesian spatial models using the integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) approaches