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Spatial And Spatio Temporal Geostatistical Modeling And Kriging

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Spatial And Spatio Temporal Geostatistical Modeling And Kriging

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Author : José-María Montero
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-17

Spatial And Spatio Temporal Geostatistical Modeling And Kriging written by José-María Montero 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 2015-08-17 with Mathematics categories.

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

Spatial And Spatio Temporal Geostatistical Modeling And Kriging

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Author : José María Montero
language : en
Publisher: John Wiley and Sons Incorporated
Release Date : 2015

Spatial And Spatio Temporal Geostatistical Modeling And Kriging written by José María Montero and has been published by John Wiley and Sons Incorporated this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Geology categories.

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.

Spatial And Spatio Temporal Geostatistical Modeling And Kriging

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Author : José-María Montero
language : en
Publisher: John Wiley & Sons
Release Date : 2015-08-18

Bayesian Modeling Of Spatio Temporal Data With R

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Author : Sujit Sahu
language : en
Publisher: CRC Press
Release Date : 2022-03-01

Bayesian Modeling Of Spatio Temporal Data With R written by Sujit Sahu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-01 with Mathematics categories.

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.

Geostatistical Functional Data Analysis

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Author : Jorge Mateu
language : en
Publisher: John Wiley & Sons
Release Date : 2021-12-13

Geostatistical Functional Data Analysis written by Jorge Mateu 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 2021-12-13 with Social Science categories.

Geostatistical Functional Data Analysis Explore the intersection between geostatistics and functional data analysis with this insightful new reference Geostatistical Functional Data Analysis presents a unified approach to modelling functional data when spatial and spatio-temporal correlations are present. The Editors link together the wide research areas of geostatistics and functional data analysis to provide the reader with a new area called geostatistical functional data analysis that will bring new insights and new open questions to researchers coming from both scientific fields. This book provides a complete and up-to-date account to deal with functional data that is spatially correlated, but also includes the most innovative developments in different open avenues in this field. Containing contributions from leading experts in the field, this practical guide provides readers with the necessary tools to employ and adapt classic statistical techniques to handle spatial regression. The book also includes: A thorough introduction to the spatial kriging methodology when working with functions A detailed exposition of more classical statistical techniques adapted to the functional case and extended to handle spatial correlations Practical discussions of ANOVA, regression, and clustering methods to explore spatial correlation in a collection of curves sampled in a region In-depth explorations of the similarities and differences between spatio-temporal data analysis and functional data analysis Aimed at mathematicians, statisticians, postgraduate students, and researchers involved in the analysis of functional and spatial data, Geostatistical Functional Data Analysis will also prove to be a powerful addition to the libraries of geoscientists, environmental scientists, and economists seeking insightful new knowledge and questions at the interface of geostatistics and functional data analysis.

On Spatio Temporal Data Modelling And Uncertainty Quantification Using Machine Learning And Information Theory

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Author : Fabian Guignard
language : en
Publisher: Springer Nature
Release Date : 2022-03-12

On Spatio Temporal Data Modelling And Uncertainty Quantification Using Machine Learning And Information Theory written by Fabian Guignard and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-12 with Science categories.

The gathering and storage of data indexed in space and time are experiencing unprecedented growth, demanding for advanced and adapted tools to analyse them. This thesis deals with the exploration and modelling of complex high-frequency and non-stationary spatio-temporal data. It proposes an efficient framework in modelling with machine learning algorithms spatio-temporal fields measured on irregular monitoring networks, accounting for high dimensional input space and large data sets. The uncertainty quantification is enabled by specifying this framework with the extreme learning machine, a particular type of artificial neural network for which analytical results, variance estimation and confidence intervals are developed. Particular attention is also paid to a highly versatile exploratory data analysis tool based on information theory, the Fisher-Shannon analysis, which can be used to assess the complexity of distributional properties of temporal, spatial and spatio-temporal data sets. Examples of the proposed methodologies are concentrated on data from environmental sciences, with an emphasis on wind speed modelling in complex mountainous terrain and the resulting renewable energy assessment. The contributions of this thesis can find a large number of applications in several research domains where exploration, understanding, clustering, interpolation and forecasting of complex phenomena are of utmost importance.

Multivariate Geostatistics

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Author : Hans Wackernagel
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-04-17

Multivariate Geostatistics written by Hans Wackernagel 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 2013-04-17 with Science categories.

This fully revised third edition introduces geostatistics by emphasising the multivariate aspects for scientists, engineers and statisticians. Geostatistics offers a variety of models, methods and techniques for the analysis, estimation and display of multivariate data distributed in space or time. The text contains a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of 3 basic methods of multivariate analysis. Applications from different areas of science, as well as exercises with solutions, are provided to help convey the general ideas. The introductory chapter has been divided into two separate sections for clarity. The final section deals with non-stationary geostatistics.

Basic Steps In Geostatistics The Variogram And Kriging

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Author : Margaret A. Oliver
language : en
Publisher: Springer
Release Date : 2015-03-30

Basic Steps In Geostatistics The Variogram And Kriging written by Margaret A. Oliver and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-30 with Technology & Engineering categories.

This brief will provide a bridge in succinct form between the geostatistics textbooks and the computer manuals for `push-button' practice. It is becoming increasingly important for practitioners, especially neophytes, to understand what underlies modern geostatistics and the currently available software so that they can choose sensibly and draw correct conclusions from their analysis and mapping. The brief will contain some theory, but only that needed for practitioners to understand the essential steps in analyses. It will guide readers sequentially through the stages of properly designed sampling, exploratory data analysis, variography (computing the variogram and modelling it), followed by ordinary kriging and finally mapping kriged estimates and their errors. There will be short section on trend and universal kriging. Other types of kriging will be mentioned so that readers can delve further in the substantive literature to tackle more complex tasks.

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.

Case Studies In Geospatial Applications To Groundwater Resources

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Author : Pravat Kumar Shit
language : en
Publisher: Elsevier
Release Date : 2022-10-21

Case Studies In Geospatial Applications To Groundwater Resources written by Pravat Kumar Shit and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Science categories.

Case Studies in Geospatial Applications to Groundwater Resources provides thorough the most up-to-date techniques in GIS and geostatistics as they relate to groundwater, through detailed case studies that prove real-world applications of remote sensing applications to this subject. Groundwater is the primary source of fresh water in many parts of the world, while come regions are becoming overly dependent on it, consuming groundwater faster than it is naturally replenished and causing water tables to decline unremittingly. India is the largest user of groundwater in the world followed by China and the USA, with developing countries using groundwater at an unsustainable rate. Systematic planning of groundwater usage using modern techniques is essential for the proper utilization, management and modeling of this precious but shrinking natural resource. With the advent of powerful and highspeed personal computers, efficient techniques for water management have evolved, of which remote sensing, GIS (Geographic Information Systems), GPS (Global Positioning Systems) and Geostatistical techniques are of great significance. This book advances the scientific understanding, development, and application of geospatial technologies related to water resource management. Case Studies in Geospatial Applications to Groundwater Resources is a valuable reference for researchers and postgraduate students in Earth and Environmental Sciences, especially GIS, agriculture, hydrology, natural resources, and soil science, who need to be able to apply the latest technologies in groundwater research in a practical manner. - Provides detailed case studies on groundwater resources around the world, including regions with highest groundwater resource use - Covers modern remote sensing and geostatistical technique-based groundwater resource mapping, monitoring, and modelling - Describes novel region-specific management strategies and techniques for sustainability with case studies to illustrate effectiveness - Includes practical coverage of the use of geospatial analysis techniques in groundwater resources

Spatial And Spatio Temporal Geostatistical Modeling And Kriging

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