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Author : Li Zhu
Publisher :
ISBN 13 :
Total Pages : 336 pages
Book Rating : 4.:/5 (319 download)
Download or read book Hierarchical Modeling of Spatio-temporally Misaligned Data written by Li Zhu and published by . This book was released on 2000 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Sudipto Banerjee
Publisher : Chapman and Hall/CRC
ISBN 13 : 9781584884101
Total Pages : 472 pages
Book Rating : 4.8/5 (841 download)
Download or read book Hierarchical Modeling and Analysis for Spatial Data written by Sudipto Banerjee and published by Chapman and Hall/CRC. This book was released on 2003-12-17 with total page 472 pages. Available in PDF, EPUB and Kindle. Book excerpt: Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics. Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and data analysis for spatial and spatio-temporal data. Starting with overviews of the types of spatial data, the data analysis tools appropriate for each, and a brief review of the Bayesian approach to statistics, the authors discuss hierarchical modeling for univariate spatial response data, including Bayesian kriging and lattice (areal data) modeling. They then consider the problem of spatially misaligned data, methods for handling multivariate spatial responses, spatio-temporal models, and spatial survival models. The final chapter explores a variety of special topics, including spatially varying coefficient models. This book provides clear explanations, plentiful illustrations --some in full color--a variety of homework problems, and tutorials and worked examples using some of the field's most popular software packages.. Written by a team of leaders in the field, it will undoubtedly remain the primary textbook and reference on the subject for years to come.
Author : Sudipto Banerjee
Publisher : CRC Press
ISBN 13 : 1439819173
Total Pages : 587 pages
Book Rating : 4.4/5 (398 download)
Download or read book Hierarchical Modeling and Analysis for Spatial Data, Second Edition written by Sudipto Banerjee and published by CRC Press. This book was released on 2014-09-12 with total page 587 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area of application. New to the Second Edition New chapter on spatial point patterns developed primarily from a modeling perspective New chapter on big data that shows how the predictive process handles reasonably large datasets New chapter on spatial and spatiotemporal gradient modeling that incorporates recent developments in spatial boundary analysis and wombling New chapter on the theoretical aspects of geostatistical (point-referenced) modeling Greatly expanded chapters on methods for multivariate and spatiotemporal modeling New special topics sections on data fusion/assimilation and spatial analysis for data on extremes Double the number of exercises Many more color figures integrated throughout the text Updated computational aspects, including the latest version of WinBUGS, the new flexible spBayes software, and assorted R packages The Only Comprehensive Treatment of the Theory, Methods, and Software This second edition continues to provide a complete treatment of the theory, methods, and application of hierarchical modeling for spatial and spatiotemporal data. It tackles current challenges in handling this type of data, with increased emphasis on observational data, big data, and the upsurge of associated software tools. The authors also explore important application domains, including environmental science, forestry, public health, and real estate.
Author : Sudipto Banerjee
Publisher : CRC Press
ISBN 13 : 1135438080
Total Pages : 470 pages
Book Rating : 4.1/5 (354 download)
Download or read book Hierarchical Modeling and Analysis for Spatial Data written by Sudipto Banerjee and published by CRC Press. This book was released on 2003-12-17 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis,
Author : Jihyeon Kwon
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (137 download)
Download or read book A Spatio-temporal Hierarchical Model to Account for Uncertainty in American Community Survey Explanatory Variables written by Jihyeon Kwon and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The American Community Survey (ACS) is one of the most vital public sources for demographic and socioeconomic characteristics of communities in the U.S. administered by the U.S. Census Bureau every year. The ACS provides communities with timely information by publishing 1-year and 5-year ACS time-period estimates. However, the time-period estimates may not adequately represent the yearly trend because they take an average over the multi-year period and are subject to uncertainty due to the sampling design. Many epidemiology and public health studies use the ACS estimates as explanatory variables in the models. However, using the ACS estimates as explanatory variables ignores the uncertainty in the time-period estimate and may disguise temporal volatility due to averaging over the time period. Our study will propose a model that accounts for the uncertainty in the ACS time-period estimates and disentangle the temporal misalignment in the multi-year time-period estimates. In order to achieve this goal, we will use a Bayesian hierarchical model that accounts for spatial or spatio-temporal dependency in data. We present the approach by modeling the prevalence of frequent mental distress in North Carolina from 2014 to 2018.
Author : Noel Cressie
Publisher : John Wiley & Sons
ISBN 13 : 1119243068
Total Pages : 596 pages
Book Rating : 4.1/5 (192 download)
Download or read book Statistics for Spatio-Temporal Data written by Noel Cressie and published by John Wiley & Sons. This book was released on 2015-11-02 with total page 596 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Author : Sara Zapata-Marin
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (135 download)
Download or read book Land-use Regression and Spatio-temporal Hierarchical Models for Environmental Processes written by Sara Zapata-Marin and published by . This book was released on 2022 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Land-use regression is a popular method used to describe the spatial variability of different environmental processes using local variables. However, there are situations in which there might be some complex spatio-temporal structure left after accounting for land-use variables.In this work, three different Bayesian hierarchical models are proposed to model the spatial and spatio-temporal dispersion of air pollutants and aeroallergens within cities. Bayesian inference can easily accommodate complex interactions while naturally accounting for uncertainties in the estimation of unknowns in the model when performing predictions.In the first study, a spatial hierarchical model is used to analyze the concentration of volatile organic compounds (VOCs) in Montreal, Canada. The data consists of concentration measurements of five VOCs measured over two-week periods for three monitoring campaigns between 2005 and 2006 over 130 locations in the city. The five VOCs of interest are: benzene, decane, ethylbenzene, hexane, and trimethylbenzene. Four different models are fitted to each of the five VOCs. These models extend land-use regression by accounting for any spatial structure left after including the covariates while also capturing the across campaign variation through an indicator variable or campaign-specific coefficients. Predicted surfaces are obtained for each campaign. For all VOCs higher levels are found during the December campaign, and the predicted areas with the highest levels correspond to multiple sections of major highways.For the second and third studies, we have available data on the daily and weekly measurements of pollen concentration in Toronto, Canada collected in 2018. The measurements consist of tree, weed, grass, and total pollen concentration at 18 monitoring sites and were obtained daily for eleven of these sites and weekly for the other seven sites.In the second study, the weekly concentration of each of the four pollen types is modeled. Instead of considering the temporal window that only has positive values, that is, removing the zeros, a hurdle model is proposed to account for the high number of measurements equal to zero. This structure allows for the estimation of the probability of the pollen concentration being equal to zero at any given week, which provides further information on temporal windows with positive concentrations of the different types of pollen. Additionally, a dynamic linear model is used to capture the weekly trend of pollen concentration in the city.In the third study, the daily concentration of total pollen is modeled. Rather than aggregating the data to the weekly scale, a temporal misalignment model is proposed to account for the difference in scale and to take advantage of the daily measurements. Using the properties of dynamic linear models and the multivariate normal distribution, a spatio-temporal model to account for temporal misalignment is proposed. This model allows to estimate the fine-scale measurements at locations where only coarse-scale observations were available. Additionally, the model is fitted to artificial data with different temporal structures, including trend and seasonality.The predicted surfaces obtained in these three studies will help inform future health-related studies. Furthermore, the methods proposed here are flexible, easily adaptable, and can improve our understanding of similar environmental processes. All codes are publicly available such that the implementation of the proposed approach in similar situations is easily achieved"--
Author : Marta Blangiardo
Publisher : John Wiley & Sons
ISBN 13 : 1118326555
Total Pages : 322 pages
Book Rating : 4.1/5 (183 download)
Download or read book Spatial and Spatio-temporal Bayesian Models with R - INLA written by Marta Blangiardo and published by John Wiley & Sons. This book was released on 2015-06-02 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatial and Spatio-Temporal Bayesian Models with R-INLA provides a much needed, practically oriented & innovative presentation of the combination of Bayesian methodology and spatial statistics. The authors combine an introduction to Bayesian theory and methodology with a focus on the spatial and spatio-temporal models used within the Bayesian framework and a series of practical examples which allow the reader to link the statistical theory presented to real data problems. The numerous examples from the fields of epidemiology, biostatistics and social science all are coded in the R package R-INLA, which has proven to be a valid alternative to the commonly used Markov Chain Monte Carlo simulations
Author : Lei Kang
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (68 download)
Download or read book Reduced-dimension Hierarchical Statistical Models for Spatial and Spatio-temporal Data written by Lei Kang and published by . This book was released on 2009 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Moreover, we extend the SRE model to the Spatio-Temporal Random Effects (STRE) model for massive spatio-temporal datasets. We explicitly model the measurement error, the non-dynamic fine-scale variation, the dynamic spatial variation, and the trend. The optimal spatio-temporal predictions are derived efficiently through the fixed-rank model and a rapid recursive updating procedure through the Kalman filter. Formulas for optimal smoothing, filtering, and forecasting are derived. The improvement of combining past and current data using the methodology called Fixed Rank Filtering (FRF) to predict the current hidden process of interest, is illustrated with a simulation experiment. The methodology is also applied to a large spatio-temporal remote-sensing dataset.
Author : Alan E. Gelfand
Publisher : CRC Press
ISBN 13 : 1498752128
Total Pages : 876 pages
Book Rating : 4.4/5 (987 download)
Download or read book Handbook of Environmental and Ecological Statistics written by Alan E. Gelfand and published by CRC Press. This book was released on 2019-01-15 with total page 876 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.
Author : Andrew B. Lawson
Publisher : CRC Press
ISBN 13 : 1584888415
Total Pages : 364 pages
Book Rating : 4.5/5 (848 download)
Download or read book Bayesian Disease Mapping written by Andrew B. Lawson and published by CRC Press. This book was released on 2008-08-05 with total page 364 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling in Spatial Epidemiology provides an overview of the main areas of Bayesian hierarchical modeling and its application to the geographical analysis of disease. The book explores a range of topics in Bayesian inference and
Author : James S. Clark
Publisher : OUP Oxford
ISBN 13 : 0191513849
Total Pages : 216 pages
Book Rating : 4.1/5 (915 download)
Download or read book Hierarchical Modelling for the Environmental Sciences written by James S. Clark and published by OUP Oxford. This book was released on 2006-05-04 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: New statistical tools are changing the ways in which scientists analyze and interpret data and models. Many of these are emerging as a result of the wide availability of inexpensive, high speed computational power. In particular, hierarchical Bayes and Markov Chain Monte Carlo methods for analysis provide consistent framework for inference and prediction where information is heterogeneous and uncertain, processes are complex, and responses depend on scale. Nowhere are these methods more promising than in the environmental sciences. Models have developed rapidly, and there is now a requirement for a clear exposition of the methodology through to application for a range of environmental challenges.
Author : Paula Moraga
Publisher : CRC Press
ISBN 13 : 1000732150
Total Pages : 217 pages
Book Rating : 4.0/5 (7 download)
Download or read book Geospatial Health Data written by Paula Moraga and published by CRC Press. This book was released on 2019-11-26 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Geospatial health data are essential to inform public health and policy. These data can be used to quantify disease burden, understand geographic and temporal patterns, identify risk factors, and measure inequalities. Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny describes spatial and spatio-temporal statistical methods and visualization techniques to analyze georeferenced health data in R. The book covers the following topics: Manipulate and transform point, areal, and raster data, Bayesian hierarchical models for disease mapping using areal and geostatistical data, Fit and interpret spatial and spatio-temporal models with the Integrated Nested Laplace Approximations (INLA) and the Stochastic Partial Differential Equation (SPDE) approaches, Create interactive and static visualizations such as disease maps and time plots, Reproducible R Markdown reports, interactive dashboards, and Shiny web applications that facilitate the communication of insights to collaborators and policy makers. The book features fully reproducible examples of several disease and environmental applications using real-world data such as malaria in The Gambia, cancer in Scotland and USA, and air pollution in Spain. Examples in the book focus on health applications, but the approaches covered are also applicable to other fields that use georeferenced data including epidemiology, ecology, demography or criminology. The book provides clear descriptions of the R code for data importing, manipulation, modeling and visualization, as well as the interpretation of the results. This ensures contents are fully reproducible and accessible for students, researchers and practitioners.
Author : Emmanuel Lesaffre
Publisher : John Wiley & Sons
ISBN 13 : 0470018232
Total Pages : 544 pages
Book Rating : 4.4/5 (7 download)
Download or read book Bayesian Biostatistics written by Emmanuel Lesaffre and published by John Wiley & Sons. This book was released on 2012-08-13 with total page 544 pages. Available in PDF, EPUB and Kindle. Book excerpt: The growth of biostatistics has been phenomenal in recent years and has been marked by considerable technical innovation in both methodology and computational practicality. One area that has experienced significant growth is Bayesian methods. The growing use of Bayesian methodology has taken place partly due to an increasing number of practitioners valuing the Bayesian paradigm as matching that of scientific discovery. In addition, computational advances have allowed for more complex models to be fitted routinely to realistic data sets. Through examples, exercises and a combination of introductory and more advanced chapters, this book provides an invaluable understanding of the complex world of biomedical statistics illustrated via a diverse range of applications taken from epidemiology, exploratory clinical studies, health promotion studies, image analysis and clinical trials. Key Features: Provides an authoritative account of Bayesian methodology, from its most basic elements to its practical implementation, with an emphasis on healthcare techniques. Contains introductory explanations of Bayesian principles common to all areas of application. Presents clear and concise examples in biostatistics applications such as clinical trials, longitudinal studies, bioassay, survival, image analysis and bioinformatics. Illustrated throughout with examples using software including WinBUGS, OpenBUGS, SAS and various dedicated R programs. Highlights the differences between the Bayesian and classical approaches. Supported by an accompanying website hosting free software and case study guides. Bayesian Biostatistics introduces the reader smoothly into the Bayesian statistical methods with chapters that gradually increase in level of complexity. Master students in biostatistics, applied statisticians and all researchers with a good background in classical statistics who have interest in Bayesian methods will find this book useful.
Author : Marc Kery
Publisher : Academic Press
ISBN 13 : 0128097272
Total Pages : 820 pages
Book Rating : 4.1/5 (28 download)
Download or read book Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS written by Marc Kery and published by Academic Press. This book was released on 2020-10-10 with total page 820 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and Advanced Models provides a synthesis of the state-of-the-art in hierarchical models for plant and animal distribution, also focusing on the complex and more advanced models currently available. The book explains all procedures in the context of hierarchical models that represent a unified approach to ecological research, thus taking the reader from design, through data collection, and into analyses using a very powerful way of synthesizing data. Makes ecological modeling accessible to people who are struggling to use complex or advanced modeling programs Synthesizes current ecological models and explains how they are inter-connected Contains numerous examples throughout the book, walking the reading through scenarios with both real and simulated data Provides an ideal resource for ecologists working in R software and in BUGS software for more flexible Bayesian analyses
Author : Birgir Hrafnkelsson
Publisher : Springer Nature
ISBN 13 : 3031397916
Total Pages : 256 pages
Book Rating : 4.0/5 (313 download)
Download or read book Statistical Modeling Using Bayesian Latent Gaussian Models written by Birgir Hrafnkelsson and published by Springer Nature. This book was released on 2023-12-10 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the statistical modeling of geophysical and environmental data using Bayesian latent Gaussian models. The structure of these models is described in a thorough introductory chapter, which explains how to construct prior densities for the model parameters, how to infer the parameters using Bayesian computation, and how to use the models to make predictions. The remaining six chapters focus on the application of Bayesian latent Gaussian models to real examples in glaciology, hydrology, engineering seismology, seismology, meteorology and climatology. These examples include: spatial predictions of surface mass balance; the estimation of Antarctica’s contribution to sea-level rise; the estimation of rating curves for the projection of water level to discharge; ground motion models for strong motion; spatial modeling of earthquake magnitudes; weather forecasting based on numerical model forecasts; and extreme value analysis of precipitation on a high-dimensional grid. The book is aimed at graduate students and experts in statistics, geophysics, environmental sciences, engineering, and related fields.
Author : Margaret B. Short
Publisher :
ISBN 13 :
Total Pages : 294 pages
Book Rating : 4.:/5 (319 download)
Download or read book Topics in Hierarchical Spatial Models written by Margaret B. Short and published by . This book was released on 2003 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt:
