Modern Methodology And Applications In Spatial Temporal Modeling

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Modern Methodology and Applications in Spatial-Temporal Modeling

Gareth William Peters,Tomoko Matsui

Author : Gareth William Peters,Tomoko Matsui
Publisher : Springer
Page : 111 pages
File Size : 55,6 Mb
Release : 2016-01-08
Category : Mathematics
ISBN : 9784431553397

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Modern Methodology and Applications in Spatial-Temporal Modeling by Gareth William Peters,Tomoko Matsui Pdf

This book provides a modern introductory tutorial on specialized methodological and applied aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter deals with non-parametric Bayesian inference via a recently developed framework known as kernel mean embedding which has had a significant influence in machine learning disciplines. The second chapter takes up non-parametric statistical methods for spatial field reconstruction and exceedance probability estimation based on Gaussian process-based models in the context of wireless sensor network data. The third chapter presents signal-processing methods applied to acoustic mood analysis based on music signal analysis. The fourth chapter covers models that are applicable to time series modeling in the domain of speech and language processing. This includes aspects of factor analysis, independent component analysis in an unsupervised learning setting. The chapter moves on to include more advanced topics on generalized latent variable topic models based on hierarchical Dirichlet processes which recently have been developed in non-parametric Bayesian literature. The final chapter discusses aspects of dependence modeling, primarily focusing on the role of extreme tail-dependence modeling, copulas, and their role in wireless communications system models.

Conceptual Modeling for Traditional and Spatio-Temporal Applications

Christine Parent,Stefano Spaccapietra,Esteban Zimányi

Author : Christine Parent,Stefano Spaccapietra,Esteban Zimányi
Publisher : Springer Science & Business Media
Page : 475 pages
File Size : 49,5 Mb
Release : 2006-09-02
Category : Computers
ISBN : 9783540303268

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Conceptual Modeling for Traditional and Spatio-Temporal Applications by Christine Parent,Stefano Spaccapietra,Esteban Zimányi Pdf

From environmental management to land planning and geo-marketing, the number of application domains that may greatly benefit from using data enriched with spatio-temporal features is expanding very rapidly. This book shows that a conceptual design approach for spatio-temporal databases is both feasible and easy to apprehend. While providing a firm basis through extensive discussion of traditional data modeling concepts, the major focus of the book is on modeling spatial and temporal information.

Statistics for Spatio-Temporal Data

Noel Cressie,Christopher K. Wikle

Author : Noel Cressie,Christopher K. Wikle
Publisher : John Wiley & Sons
Page : 624 pages
File Size : 54,9 Mb
Release : 2015-11-02
Category : Mathematics
ISBN : 9781119243069

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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 statistical modeling concepts and the latest computational methods Noel Cressie and Christopher K. Wikle, are also winners of the 2011 PROSE Award in the Mathematics category, for the book “Statistics for Spatio-Temporal Data” (2011), published by John Wiley and Sons. (The PROSE awards, for Professional and Scholarly Excellence, are given by the Association of American Publishers, the national trade association of the US book publishing industry.) Statistics for Spatio-Temporal Data has now been reprinted with small corrections to the text and the bibliography. The overall content and pagination of the new printing remains the same; the difference comes in the form of corrections to typographical errors, editing of incomplete and missing references, and some updated spatio-temporal interpretations. From understanding environmental processes and climate trends to developing new technologies for mapping public-health data and the spread of invasive-species, there is a high demand for statistical analyses of data that take spatial, temporal, and spatio-temporal information into account. Statistics for Spatio-Temporal Data presents a systematic approach to key quantitative techniques that incorporate the latest advances in statistical computing as well as hierarchical, particularly Bayesian, statistical modeling, with an emphasis on dynamical spatio-temporal models. Cressie and Wikle supply a unique presentation that incorporates ideas from the areas of time series and spatial statistics as well as stochastic processes. Beginning with separate treatments of temporal data and spatial data, the book combines these concepts to discuss spatio-temporal statistical methods for understanding complex processes. Topics of coverage include: Exploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, 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 and computational algorithms for their implementation Quantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data Throughout the book, interesting applications demonstrate the relevance of the presented concepts. Vivid, full-color graphics emphasize the visual nature of the topic, and a related FTP site contains supplementary material. Statistics for Spatio-Temporal Data is an excellent book for a graduate-level course on spatio-temporal statistics. It is also a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Theoretical Aspects of Spatial-Temporal Modeling

Gareth William Peters,Tomoko Matsui

Author : Gareth William Peters,Tomoko Matsui
Publisher : Springer
Page : 124 pages
File Size : 51,5 Mb
Release : 2015-12-24
Category : Mathematics
ISBN : 9784431553366

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Theoretical Aspects of Spatial-Temporal Modeling by Gareth William Peters,Tomoko Matsui Pdf

This book provides a modern introductory tutorial on specialized theoretical aspects of spatial and temporal modeling. The areas covered involve a range of topics which reflect the diversity of this domain of research across a number of quantitative disciplines. For instance, the first chapter provides up-to-date coverage of particle association measures that underpin the theoretical properties of recently developed random set methods in space and time otherwise known as the class of probability hypothesis density framework (PHD filters). The second chapter gives an overview of recent advances in Monte Carlo methods for Bayesian filtering in high-dimensional spaces. In particular, the chapter explains how one may extend classical sequential Monte Carlo methods for filtering and static inference problems to high dimensions and big-data applications. The third chapter presents an overview of generalized families of processes that extend the class of Gaussian process models to heavy-tailed families known as alpha-stable processes. In particular, it covers aspects of characterization via the spectral measure of heavy-tailed distributions and then provides an overview of their applications in wireless communications channel modeling. The final chapter concludes with an overview of analysis for probabilistic spatial percolation methods that are relevant in the modeling of graphical networks and connectivity applications in sensor networks, which also incorporate stochastic geometry features.

Spatio-Temporal Methods in Environmental Epidemiology

Gavin Shaddick,James V. Zidek

Author : Gavin Shaddick,James V. Zidek
Publisher : CRC Press
Page : 395 pages
File Size : 48,7 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.

Modern Statistical Methods for Spatial and Multivariate Data

Norou Diawara

Author : Norou Diawara
Publisher : Springer
Page : 177 pages
File Size : 47,5 Mb
Release : 2019-06-29
Category : Mathematics
ISBN : 9783030114312

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Modern Statistical Methods for Spatial and Multivariate Data by Norou Diawara Pdf

This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.

Statistical Methods for Spatio-Temporal Systems

Barbel Finkenstadt,Leonhard Held,Valerie Isham

Author : Barbel Finkenstadt,Leonhard Held,Valerie Isham
Publisher : CRC Press
Page : 314 pages
File Size : 46,6 Mb
Release : 2006-10-20
Category : Mathematics
ISBN : 9781420011050

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Statistical Methods for Spatio-Temporal Systems by Barbel Finkenstadt,Leonhard Held,Valerie Isham Pdf

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities. Contributed by leading researchers in the field, each self-contained chapter starts w

Spatio-temporal Design

Jorge Mateu,Werner G. Müller

Author : Jorge Mateu,Werner G. Müller
Publisher : John Wiley & Sons
Page : 320 pages
File Size : 46,5 Mb
Release : 2012-11-05
Category : Mathematics
ISBN : 9781118441886

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Spatio-temporal Design by Jorge Mateu,Werner G. Müller Pdf

A state-of-the-art presentation of optimum spatio-temporal sampling design - bridging classic ideas with modern statistical modeling concepts and the latest computational methods. Spatio-temporal Design presents a comprehensive state-of-the-art presentation combining both classical and modern treatments of network design and planning for spatial and spatio-temporal data acquisition. A common problem set is interwoven throughout the chapters, providing various perspectives to illustrate a complete insight to the problem at hand. Motivated by the high demand for statistical analysis of data that takes spatial and spatio-temporal information into account, this book incorporates ideas from the areas of time series, spatial statistics and stochastic processes, and combines them to discuss optimum spatio-temporal sampling design. Spatio-temporal Design: Advances in Efficient Data Acquisition: Provides an up-to-date account of how to collect space-time data for monitoring, with a focus on statistical aspects and the latest computational methods Discusses basic methods and distinguishes between design and model-based approaches to collecting space-time data. Features model-based frequentist design for univariate and multivariate geostatistics, and second-phase spatial sampling. Integrates common data examples and case studies throughout the book in order to demonstrate the different approaches and their integration. Includes real data sets, data generating mechanisms and simulation scenarios. Accompanied by a supporting website featuring R code. Spatio-temporal Design presents an excellent book for graduate level students as well as a valuable reference for researchers and practitioners in the fields of applied mathematics, engineering, and the environmental and health sciences.

Spatio–Temporal Methods in Environmental Epidemiology with R

Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt

Author : Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt
Publisher : CRC Press
Page : 458 pages
File Size : 44,5 Mb
Release : 2023-12-12
Category : Medical
ISBN : 9781003808022

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Spatio–Temporal Methods in Environmental Epidemiology with R by Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt Pdf

Spatio-Temporal Methods in Environmental Epidemiology with R, like its First Edition, explores the interface between environmental epidemiology and spatio-temporal modeling. It links recent developments in spatio-temporal theory with epidemiological applications. Drawing on real-life problems, it shows how recent advances in methodology can assess the health risks associated with environmental hazards. The book's clear guidelines enable the implementation of the methodology and estimation of risks in practice. New additions to the Second Edition include: a thorough exploration of the underlying concepts behind knowledge discovery through data; a new chapter on extracting information from data using R and the tidyverse; additional material on methods for Bayesian computation, including the use of NIMBLE and Stan; new methods for performing spatio-temporal analysis and an updated chapter containing further topics. Throughout the book there are new examples, and the presentation of R code for examples has been extended. Along with these additions, the book now has a GitHub site (https://spacetime-environ.github.io/stepi2) that contains data, code and further worked examples. Features: • Explores the interface between environmental epidemiology and spatio-temporal modeling • Incorporates examples that show how spatio-temporal methodology can inform societal concerns about the effects of environmental hazards on health • Uses a Bayesian foundation on which to build an integrated approach to spatio-temporal modeling and environmental epidemiology • Discusses data analysis and topics such as data visualization, mapping, wrangling and analysis • Shows how to design networks for monitoring hazardous environmental processes and the ill effects of preferential sampling • Through the listing and application of code, shows the power of R, tidyverse, NIMBLE and Stan and other modern tools in performing complex data analysis and modeling Representing a continuing important 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. Readers will learn how to identify and model patterns in spatio-temporal data and how to exploit dependencies over space and time to reduce bias and inefficiency when estimating risks to health.

Spatio-Temporal Statistics with R

Christopher K. Wikle,Andrew Zammit-Mangion,Noel Cressie

Author : Christopher K. Wikle,Andrew Zammit-Mangion,Noel Cressie
Publisher : CRC Press
Page : 380 pages
File Size : 42,6 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.

Regression Modelling Wih Spatial and Spatial-Temporal Data

Robert P. Haining,Guangquan Li

Author : Robert P. Haining,Guangquan Li
Publisher : Chapman & Hall/CRC
Page : 592 pages
File Size : 49,8 Mb
Release : 2019
Category : Bayesian statistical decision theory
ISBN : 1482237423

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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. Robert Haining is Emeritus Professor in Human Geography, University of Cambridge, England. He is the author of Spatial Data Analysis in the Social and Environmental Sciences (1990) and Spatial Data Analysis: Theory and Practice (2003). He is a Fellow of the RGS-IBG and of the Academy of Social Sciences. Guangquan Li is Senior Lecturer in Statistics in Department of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle, England. His research includes the development and application of Bayesian methods in the social and health sciences. He is a Fellow of the Royal Statistical Society.

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

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 : 52,7 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 with R

Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt

Author : Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt
Publisher : Unknown
Page : 0 pages
File Size : 48,8 Mb
Release : 2024
Category : Environmental health
ISBN : 1032403519

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Spatio-temporal Methods in Environmental Epidemiology with R by Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt Pdf

"Spatio-Temporal Methods in Environmental Epidemiology with R, Second Edition 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 MED, 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. New to this edition: Includes a new chapter on data science Updated material on measurement error, deterministic modeling, infectious diseases, and preferential sampling Introduces modern computational methods, including INLA, together with code for implementation Represents a major new direction in environmental epidemiology, this book-in full color throughout-underscoring 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"--

Spatial and Spatio-Temporal Geostatistical Modeling and Kriging

José-María Montero,Gema Fernández-Avilés,Jorge Mateu

Author : José-María Montero,Gema Fernández-Avilés,Jorge Mateu
Publisher : John Wiley & Sons
Page : 400 pages
File Size : 42,5 Mb
Release : 2015-08-19
Category : Mathematics
ISBN : 9781118762424

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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

Handbook of Discrete-Valued Time Series

Richard A. Davis,Scott H. Holan,Robert Lund,Nalini Ravishanker

Author : Richard A. Davis,Scott H. Holan,Robert Lund,Nalini Ravishanker
Publisher : CRC Press
Page : 484 pages
File Size : 42,8 Mb
Release : 2016-01-06
Category : Mathematics
ISBN : 9781466577749

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Handbook of Discrete-Valued Time Series by Richard A. Davis,Scott H. Holan,Robert Lund,Nalini Ravishanker Pdf

Model a Wide Range of Count Time Series Handbook of Discrete-Valued Time Series presents state-of-the-art methods for modeling time series of counts and incorporates frequentist and Bayesian approaches for discrete-valued spatio-temporal data and multivariate data. While the book focuses on time series of counts, some of the techniques discussed ca

Modern Methodology And Applications In Spatial Temporal Modeling

Modern Methodology and Applications in Spatial-Temporal Modeling by Gareth William Peters,Tomoko Matsui Pdf

Conceptual Modeling for Traditional and Spatio-Temporal Applications by Christine Parent,Stefano Spaccapietra,Esteban Zimányi Pdf

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

Theoretical Aspects of Spatial-Temporal Modeling by Gareth William Peters,Tomoko Matsui Pdf

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

Modern Statistical Methods for Spatial and Multivariate Data by Norou Diawara Pdf

Statistical Methods for Spatio-Temporal Systems by Barbel Finkenstadt,Leonhard Held,Valerie Isham Pdf

Spatio-temporal Design by Jorge Mateu,Werner G. Müller Pdf

Spatio–Temporal Methods in Environmental Epidemiology with R by Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt Pdf

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

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

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

Spatio-temporal Methods in Environmental Epidemiology with R by Gavin Shaddick,James V. Zidek,Alexandra M. Schmidt Pdf

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

Handbook of Discrete-Valued Time Series by Richard A. Davis,Scott H. Holan,Robert Lund,Nalini Ravishanker Pdf

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