Model Based Geostatistics For Global Public Health
DOWNLOAD
Download Model Based Geostatistics For Global Public Health PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Model Based Geostatistics For Global Public Health book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Model Based Geostatistics For Global Public Health
DOWNLOAD
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 For Global Public Health
DOWNLOAD
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.
Mapping Global Justice
DOWNLOAD
Author : Arnaud Kurze
language : en
Publisher: Taylor & Francis
Release Date : 2022-10-14
Mapping Global Justice written by Arnaud Kurze and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-14 with Political Science categories.
Persistent international conflicts, increasing inequality in many regions or the world, and acute environmental and climate-related threats to humanity call for a better understanding of the processes, actors and tools available to face the challenges of achieving global justice. This book offers a broad and multidisciplinary survey of global justice, bridging the gap between theory and practice by connecting conceptual frameworks with a panoply of case studies and an in-depth discussion of practical challenges. Connecting these critical aspects to larger moral and ethical debates is essential for thinking about large, abstract ideas and applying them directly to specific contexts. Core content includes: Key debates in global justice from across philosophy, postcolonial studies, political science, sociology and criminology The origins of global justice and the development of the human rights agenda; peacekeeping and post-conflict studies Global poverty and sustainable development Global security and transnational crime Environmental justice, public health and well-being Rather than providing a blueprint for the practice of global justice, this text problematizes efforts to cope with many justice related issues. The pedagogical approach is designed to map the difficulties that exist between theory and praxis, encourage critical thinking and fuel debates to help seek alternative solutions. Bringing together perspectives from a wealth of disciplines, this book is essential reading for courses on global justice across criminology, sociology, political science, anthropology, philosophy and law.
Model Based Monitoring And Statistical Control
DOWNLOAD
Author : Kohei Ohtsu
language : en
Publisher: CRC Press
Release Date : 2024-06-11
Model Based Monitoring And Statistical Control written by Kohei Ohtsu and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-11 with Mathematics categories.
Available in English for the first time, this classic and influential book by the late Kohei Ohtsu presents real examples of ships in motion under irregular ocean waves, how to understand the characteristics of fluctuations of stochastic phenomena through spectral analysis methods and statistical modeling. It also explains how to realize prediction and optimal control based on time series models. In recent years, the need to improve safety and reduce environmental impact in ship operations has been increasing, and the statistical methods presented in this book will be increasingly needed in the future. In addition, the recent development of innovative AI technology and highspeed communications will make it possible to adapt this method not only to ship monitoring and control, but also to any field that involves irregular fluctuations, and it is expected to contribute to solving issues that have been difficult to solve in the past. Part 1 describes classical spectral method for the analysis of stochastic phenomena. In Part 2, this book explains methods to construct time series models using the information criterion, to capture the characteristics of ship and engine motions using the model, to design a model-based monitoring system that informs navigators operating the ship and managers ashore. Furthermore, it explains statistical control method to design an autopilot system and the governor of a marine engine, while showing actual examples. Part 3 presents the basic knowledge necessary for understanding these topics of the book, namely, the basic theory of ship motion, probability and statistics, Kalman filter and statistical optimal control theory.
Bayesian Spatial Modelling With Conjugate Prior Models
DOWNLOAD
Author : Henning Omre
language : en
Publisher: Springer Nature
Release Date : 2024-10-03
Bayesian Spatial Modelling With Conjugate Prior Models written by Henning Omre and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-03 with Mathematics categories.
This book offers a comprehensive overview of statistical methodology for modelling and evaluating spatial variables useful in a variety of applications. These spatial variables fall into three categories: continuous, like terrain elevation; events, like tree locations; and mosaics, like medical images. Definitions and discussions of random field models are included for each of these three previously mentioned spatial variable types. Moreover, the readers will have access to algorithms suitable for applying this methodology in practical problem solving, and the computational efficiency of these algorithms are discussed. The presentation is made in a consistent predictive Bayesian framework, which allows separate modelling of the observation acquisition procedure, as a likelihood model, and of the spatial variable characteristics, as a prior spatial model. The likelihood and prior models uniquely define the posterior spatial model, which provides the basis for spatial simulations, spatial predictions with associated precisions, and model parameter inference. The emphasis is on Bayesian spatial modelling with conjugate pairs of likelihood and prior models that are analytically tractable and hence suitable for data abundant spatial studies. Alternative methods frequently used in spatial statistics are presented using a unified notation. The book is suitable as a textbook for a ‘Spatial Statistics’ course at the MSc or PhD level, as it also includes algorithm descriptions, project texts, and exercises.
Epidemiology Of Brain And Spinal Tumors
DOWNLOAD
Author : Jahangir Moini
language : en
Publisher: Academic Press
Release Date : 2021-04-09
Epidemiology Of Brain And Spinal Tumors written by Jahangir Moini and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-09 with Medical categories.
Epidemiology of Brain and Spinal Tumors provides a single volume resource on imaging methods and neuroepidemiology of both brain and spinal tumors. The book covers a variety of imaging techniques, including computed tomography (CT), MRI, positron emission tomography (PET), and other laboratory tests used in diagnosis and treatment. Detailed epidemiology, various imaging methods, and clinical considerations of tumors of the CNS make this an ideal reference for users who will also find diverse information about structures and functions, cytology, epidemiology (including molecular epidemiology), diagnosis and treatment. This book is appropriate for neuroscience researchers, medical professionals and anyone interested in a complete guide to visualizing and understanding CNS tumors. - Provides the most up-to-date information surrounding the epidemiology, biology and imaging techniques for brain and spinal tumors, including CT, MRI, PET, and others - Includes full color figures, photos, tables, graphs and radioimaging - Contains information that will be valuable to anyone interested in the field of neurooncology and the treatment of patients with brain and spinal tumors - Serves as a source of background information for basic scientists and pharmaceutical researchers who have an interest in imaging and treatment
Spatial Analysis
DOWNLOAD
Author : John T. Kent
language : en
Publisher: John Wiley & Sons
Release Date : 2022-05-31
Spatial Analysis written by John T. Kent 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 2022-05-31 with Mathematics categories.
SPATIAL ANALYSIS Explore the foundations and latest developments in spatial statistical analysis In Spatial Analysis, two distinguished authors deliver a practical and insightful exploration of the statistical investigation of the interdependence of random variables as a function of their spatial proximity. The book expertly blends theory and application, offering numerous worked examples and exercises at the end of each chapter. Increasingly relevant to fields as diverse as epidemiology, geography, geology, image analysis, and machine learning, spatial statistics is becoming more important to a wide range of specialists and professionals. The book includes: Thorough introduction to stationary random fields, intrinsic and generalized random fields, and stochastic models Comprehensive exploration of the estimation of spatial structure Practical discussion of kriging and the spatial linear model Spatial Analysis is an invaluable resource for advanced undergraduate and postgraduate students in statistics, data science, digital imaging, geostatistics, and agriculture. It’s also an accessible reference for professionals who are required to use spatial models in their work.
Advances In Agronomy
DOWNLOAD
Author :
language : en
Publisher: Elsevier
Release Date : 2024-09-11
Advances In Agronomy written by and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-11 with Technology & Engineering categories.
Advances in Agronomy, Volume 188, the latest release in this leading reference on agronomy, contains a variety of updates and highlights new advances in the field, each written by an international board of authors. - Includes numerous, timely, state-of-the-art reviews on the latest advancements in agronomy - Features distinguished, well recognized authors from around the world - Builds upon this venerable and iconic review series - Covers the extensive variety and breadth of subject matter in the crop and soil sciences
Geostatistical Functional Data Analysis
DOWNLOAD
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.
Bayesian Modeling Of Spatio Temporal Data With R
DOWNLOAD
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.