Modern Methodology And Applications In Spatial Temporal Modeling

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Modern Methodology And Applications In Spatial Temporal Modeling

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Author : Gareth William Peters
language : en
Publisher: Springer
Release Date : 2016-01-08

Modern Methodology And Applications In Spatial Temporal Modeling written by Gareth William Peters and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-01-08 with Mathematics categories.

​ 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.

Theoretical Aspects Of Spatial Temporal Modeling

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Author : Gareth William Peters
language : en
Publisher: Springer
Release Date : 2015-12-24

Theoretical Aspects Of Spatial Temporal Modeling written by Gareth William Peters and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-24 with Mathematics categories.

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.

Statistics For Spatio Temporal Data

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Author : Noel Cressie
language : en
Publisher: John Wiley & Sons
Release Date : 2015-11-02

Statistics For Spatio Temporal Data written by Noel Cressie 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 2015-11-02 with Mathematics categories.

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.

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

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 2015-08-18 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

Advances In Dynamics Optimization And Computation

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Author : Oliver Junge
language : en
Publisher: Springer Nature
Release Date : 2020-07-20

Advances In Dynamics Optimization And Computation written by Oliver Junge and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-20 with Technology & Engineering categories.

This book presents a collection of papers on recent advances in problems concerning dynamics, optimal control and optimization. In many chapters, computational techniques play a central role. Set-oriented techniques feature prominently throughout the book, yielding state-of-the-art algorithms for computing general invariant sets, constructing globally optimal controllers and solving multi-objective optimization problems.

Spatio Temporal Methods In Environmental Epidemiology

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Author : Gavin Shaddick
language : en
Publisher: CRC Press
Release Date : 2015-06-17

Spatio Temporal Methods In Environmental Epidemiology written by Gavin Shaddick and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-17 with Mathematics categories.

Teaches Students How to Perform Spatio-Temporal Analyses within Epidemiological StudiesSpatio-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

18th Imt Gt International Conference On Mathematics Statistics And Their Applications

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Author :
language : en
Publisher: Sciendo
Release Date : 2024-04-30

18th Imt Gt International Conference On Mathematics Statistics And Their Applications written by and has been published by Sciendo this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-30 with Computers categories.

The 18th ICMSA 2023 emphasized the critical role of statistical science in advancing the Sustainable Development Goals (SDGs). The conference highlighted how data science and statistical methods are essential for solving real-world problems and achieving sustainable development. The event aimed to enhance the research output of Universitas Syiah Kuala, foster a collaborative research environment, and facilitate scientific exchange with international scholars. By focusing on statistics, the conference sought to enhance the university's global reputation and contribute to government efforts to address health, environmental, and economic challenges through data-driven insights. ICMSA 2023 set a high standard for subsequent conferences, with a commitment to refining its structure and expanding its reach. The statistics-focused sessions attracted a large number of submissions, reflecting the dynamic nature of the statistics community. Following a thorough peer review process, 22 papers were selected for inclusion in the Book of Applied Statistics, ensuring that the conference's critical statistical research contributions were effectively captured and shared. Conference date, place 10 - 11 April 2023, Universitas Syiah Kuala, Banda Aceh, Aceh, Indonesia Conference Organizer ICMSA 2023, Statistics Department, Universitas Syiah Kuala Editor-in-Chief Latifah Rahayu Siregar, S.Si., M.Sc, Universitas Syiah Kuala, Indonesia Managing Editor Ridha Ferdhiana, S.Si., M.Sc, Universitas Syiah Kuala, Indonesia Editorial Advisory Board Prof. Dr. Ir. Marwan, Universitas Syiah Kuala, Indonesia Prof. Dr. Ir. Agussabti, M.Si., IPU., Universitas Syiah Kuala, Indonesia Dr. Ir. Taufiq S., M.Eng., IPU, Universitas Syiah Kuala, Indonesia Prof. Dr. Taufik Fuadi Abidin, S.Si., M.Tech, Universitas Syiah Kuala, Indonesia Prof. Dr. Hizir, Universitas Syiah Kuala, Indonesia Prof. Dr. Teuku Mohamad Iqbalsyah, S.Si., M.Sc, Universitas Syiah Kuala, Indonesia Yudhie Andriyana, M.Sc., PhD, FORSTAT, Indonesia Dr. Nizamuddin, M.Info.Sc, Universitas Syiah Kuala, Indonesia Dr. Nasrullah, S.Si., M.Si., M.Sc, Universitas Syiah Kuala, Indonesia Nazaruddin, S.Si., M.Eng.Sc, Universitas Syiah Kuala, Indonesia Dr. Zurnila Marli Kesuma, S.Si., M. Si, Universitas Syiah Kuala, Indonesia Prof. Dr. Herman Mawengkang, Universitas Sumatera Utara, Indonesia Editors Dr. Selvi Mardalena, S.Stat., Universitas Syiah Kuala, Indonesia Dr. Rumaisa Kruba, S.Si, Universitas Syiah Kuala, Indonesia Dr. Rahma Zuhra, Universitas Syiah Kuala, Indonesia Dr. Muhammad Subianto, M. Si, Universitas Syiah Kuala, Indonesia Dr. Saiful Mahdi, M. Sc, Universitas Syiah Kuala, Indonesia Rini Oktavia, S.Si., M.Si., Ph.D, Universitas Syiah Kuala, Indonesia Vera Halfiani, S. Si, M. Mat, Universitas Syiah Kuala, Indonesia Language Editors Fitriana AR, Universitas Syiah Kuala, Indonesia Technical Editors Novi Reandy Sasmita, S.Si., M.Sc, Universitas Syiah Kuala, Indonesia ABSTRACTING & INDEXING Baidu Scholar Bayerische Staatsbibliothek BDS BoD Bowker Book Data Ciando CNKI Scholar (China National Knowledge Infrastructure) Dimensions EBSCO ExLibris Google Books Google Scholar Naviga ReadCube Semantic Scholar TDOne (TDNet) WorldCat (OCLC) X-MOL

Spatio Temporal Methods In Environmental Epidemiology With R

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Author : Gavin Shaddick
language : en
Publisher: CRC Press
Release Date : 2023-12-12

Spatio Temporal Methods In Environmental Epidemiology With R written by Gavin Shaddick and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-12 with Medical categories.

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.

Spatiotemporal Data Analytics And Modeling

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Author : John A
language : en
Publisher: Springer Nature
Release Date : 2024-04-15

Spatiotemporal Data Analytics And Modeling written by John A and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.

With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services. A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting,and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things.

A Modal Approach To The Space Time Dynamics Of Cognitive Biomarkers

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Author : Tristan D. Griffith
language : en
Publisher: Springer Nature
Release Date : 2023-03-01

A Modal Approach To The Space Time Dynamics Of Cognitive Biomarkers written by Tristan D. Griffith and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-01 with Technology & Engineering categories.

This book develops and details a rigorous, canonical modeling approach for analyzing spatio-temporal brain wave dynamics. The nonlinear, nonstationary behavior of brain wave measures and general uncertainty associated with the brain makes it difficult to apply modern system identification techniques to such systems. While there is a substantial amount of literature on the use of stationary analyses for brain waves, relatively less work has considered real-time estimation and imaging of brain waves from noninvasive measurements. This book addresses the issue of modeling and imaging brain waves and biomarkers generally, treating the nonlinear and nonstationary dynamics in near real-time. Using a modal state-space formulation leads to intuitive, physically significant models which are used for analysis and diagnosis. A Modal Approach to the Space-Time Dynamics of Cognitive Biomarkers provides a much-needed reference for practicing researchers in biomarker modeling leveraging the lens of engineering dynamics.