Download or read book Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA written by Elias T. Krainski and published by CRC Press. This book was released on 2018-12-07 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Modelling Longitudinal and Spatially Correlated Data written by Timothy G. Gregoire and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 404 pages. Available in PDF, EPUB and Kindle. Book excerpt: Correlated data arise in numerous contexts across a wide spectrum of subject-matter disciplines. Modeling such data present special challenges and opportunities that have received increasing scrutiny by the statistical community in recent years. In October 1996 a group of 210 statisticians and other scientists assembled on the small island of Nantucket, U. S. A. , to present and discuss new developments relating to Modelling Longitudinal and Spatially Correlated Data: Methods, Applications, and Future Direc tions. Its purpose was to provide a cross-disciplinary forum to explore the commonalities and meaningful differences in the source and treatment of such data. This volume is a compilation of some of the important invited and volunteered presentations made during that conference. The three days and evenings of oral and displayed presentations were arranged into six broad thematic areas. The session themes, the invited speakers and the topics they addressed were as follows: • Generalized Linear Models: Peter McCullagh-"Residual Likelihood in Linear and Generalized Linear Models" • Longitudinal Data Analysis: Nan Laird-"Using the General Linear Mixed Model to Analyze Unbalanced Repeated Measures and Longi tudinal Data" • Spatio---Temporal Processes: David R. Brillinger-"Statistical Analy sis of the Tracks of Moving Particles" • Spatial Data Analysis: Noel A. Cressie-"Statistical Models for Lat tice Data" • Modelling Messy Data: Raymond J. Carroll-"Some Results on Gen eralized Linear Mixed Models with Measurement Error in Covariates" • Future Directions: Peter J.
Download or read book A Model of the Universe written by Storrs McCall and published by Oxford University Press. This book was released on 1994 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: He shows that this theory can illuminate a wide variety of hitherto unresolved philosophical problems: these include the direction and flow of time, the nature of scientific laws, the interpretation of quantum mechanics, the definition of probability, counterfactual semantics, and the notions of identity, essential properties, deliberation, decision, and free will.
Download or read book The Large Scale Structure of Space Time written by S. W. Hawking and published by Cambridge University Press. This book was released on 1975-02-27 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt: Einstein's General Theory of Relativity leads to two remarkable predictions: first, that the ultimate destiny of many massive stars is to undergo gravitational collapse and to disappear from view, leaving behind a 'black hole' in space; and secondly, that there will exist singularities in space-time itself. These singularities are places where space-time begins or ends, and the presently known laws of physics break down. They will occur inside black holes, and in the past are what might be construed as the beginning of the universe. To show how these predictions arise, the authors discuss the General Theory of Relativity in the large. Starting with a precise formulation of the theory and an account of the necessary background of differential geometry, the significance of space-time curvature is discussed and the global properties of a number of exact solutions of Einstein's field equations are examined. The theory of the causal structure of a general space-time is developed, and is used to study black holes and to prove a number of theorems establishing the inevitability of singualarities under certain conditions. A discussion of the Cauchy problem for General Relativity is also included in this 1973 book.
Download or read book Spatiotemporal Random Fields written by George Christakos and published by Elsevier. This book was released on 2017-07-26 with total page 696 pages. Available in PDF, EPUB and Kindle. Book excerpt: Spatiotemporal Random Fields: Theory and Applications, Second Edition, provides readers with a new and updated edition of the text that explores the application of spatiotemporal random field models to problems in ocean, earth, and atmospheric sciences, spatiotemporal statistics, and geostatistics, among others. The new edition features considerable detail of spatiotemporal random field theory, including ordinary and generalized models, as well as space-time homostationary, isostationary and hetrogeneous approaches. Presenting new theoretical and applied results, with particular emphasis on space-time determination and interpretation, spatiotemporal analysis and modeling, random field geometry, random functionals, probability law, and covariance construction techniques, this book highlights the key role of space-time metrics, the physical interpretation of stochastic differential equations, higher-order space-time variability functions, the validity of major theoretical assumptions in real-world practice (covariance positive-definiteness, metric-adequacy etc.), and the emergence of interdisciplinary phenomena in conditions of multi-sourced real-world uncertainty. Contains applications in the form of examples and case studies, providing readers with first-hand experiences Presents an easy to follow narrative which progresses from simple concepts to more challenging ideas Includes significant updates from the previous edition, including a focus on new theoretical and applied results
Download or read book Bayesian Hierarchical Space Time Models with Application to Significant Wave Height written by Erik Vanem and published by Springer Science & Business Media. This book was released on 2013-10-11 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an example of a thorough statistical treatment of ocean wave data in space and time. It demonstrates how the flexible framework of Bayesian hierarchical space-time models can be applied to oceanographic processes such as significant wave height in order to describe dependence structures and uncertainties in the data. This monograph is a research book and it is partly cross-disciplinary. The methodology itself is firmly rooted in the statistical research tradition, based on probability theory and stochastic processes. However, that methodology has been applied to a problem in the field of physical oceanography, analyzing data for significant wave height, which is of crucial importance to ocean engineering disciplines. Indeed, the statistical properties of significant wave height are important for the design, construction and operation of ships and other marine and coastal structures. Furthermore, the book addresses the question of whether climate change has an effect of the ocean wave climate, and if so what that effect might be. Thus, this book is an important contribution to the ongoing debate on climate change, its implications and how to adapt to a changing climate, with a particular focus on the maritime industries and the marine environment. This book should be of value to anyone with an interest in the statistical modelling of environmental processes, and in particular to those with an interest in the ocean wave climate. It is written on a level that should be understandable to everyone with a basic background in statistics or elementary mathematics, and an introduction to some basic concepts is provided in the appendices for the uninitiated reader. The intended readership includes students and professionals involved in statistics, oceanography, ocean engineering, environmental research, climate sciences and risk assessment. Moreover, the book’s findings are relevant for various stakeholders in the maritime industries such as design offices, classification societies, ship owners, yards and operators, flag states and intergovernmental agencies such as the IMO.
Download or read book Modelling Biological Populations in Space and Time written by Eric Renshaw and published by Cambridge University Press. This book was released on 1993-08-26 with total page 428 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume develops a unifying approach to population studies, emphasising the interplay between modelling and experimentation. Throughout, mathematicians and biologists are provided with a framework within which population dynamics can be fully explored and understood. Aspects of population dynamics covered include birth-death and logistic processes, competition and predator-prey relationships, chaos, reaction time-delays, fluctuating environments, spatial systems, velocities of spread, epidemics, and spatial branching structures. Both deterministic and stochastic models are considered. Whilst the more theoretically orientated sections will appeal to mathematical biologists, the material is presented so that readers with little mathematical expertise can bypass these without losing the main flow of the text.
Download or read book The Emergence of Spacetime in String Theory written by Tiziana Vistarini and published by Routledge. This book was released on 2019-06-12 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: The nature of space and time is one of the most fascinating and fundamental philosophical issues which presently engages at the deepest level with physics. During the last thirty years this notion has been object of an intense critical review in the light of new scientific theories which try to combine the principles of both general relativity and quantum theory—called theories of quantum gravity. This book considers the way string theory shapes its own account of spacetime disappearance from the fundamental level.
Download or read book The Mathematical Reality written by Alexander Unzicker and published by . This book was released on 2020-01-29 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Alexander Unzicker is a theoretical physicist and writes about elementary questions of natural philosophy. His critique of contemporary physics Bankrupting Physics (Macmillan) received the 'Science Book of the Year' award (German edition 2010). With The Mathematical Reality, Unzicker presents his most fundamental work to date, which is the result of years of study of natural laws and their historical development.The discovery of fundamental laws of nature has influenced the fate of Homo sapiens more than anything else. Has modern physics already understood these laws? Many puzzles formulated by Albert Einstein or Paul Dirac are still unsolved today, in particular the meaning of fundamental constants. In this book, Unzicker contends that a rational description of nature must do without any constants.A methodological and historical analysis shows, however, that the underlying problem of physics is deep, unexpected and fatal: the concepts of space and time themselves, the basis of science since Newton, could be fundamentally inappropriate for the description of reality, although-or precisely because-they are so easily accessible to human perception.A new understanding of reality can only arise from mathematics. By exploring the three-dimensional unitary sphere, which could replace the concepts of space and time, the author presents a mathematical vision that points the way to a new understanding of reality.
Download or read book Data Science written by Ivo D. Dinov and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-12-06 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: The amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
Download or read book Space Time Reference Systems written by Michael Soffel and published by Springer Science & Business Media. This book was released on 2012-10-18 with total page 321 pages. Available in PDF, EPUB and Kindle. Book excerpt: The high accuracy of modern astronomical spatial-temporal reference systems has made them considerably complex. This book offers a comprehensive overview of such systems. It begins with a discussion of ‘The Problem of Time’, including recent developments in the art of clock making (e.g., optical clocks) and various time scales. The authors address the definitions and realization of spatial coordinates by reference to remote celestial objects such as quasars. After an extensive treatment of classical equinox-based coordinates, new paradigms for setting up a celestial reference system are introduced that no longer refer to the translational and rotational motion of the Earth. The role of relativity in the definition and realization of such systems is clarified. The topics presented in this book are complemented by exercises (with solutions). The authors offer a series of files, written in Maple, a standard computer algebra system, to help readers get a feel for the various models and orders of magnitude. Beyond astrometry, the main fields of application of high-precision astronomical spatial-temporal reference systems and frames are navigation (GPS, interplanetary spacecraft navigation) and global geodynamics, which provide a high-precision Celestial Reference System and its link to any terrestrial spatial-temporal reference system. Mankind’s urgent environmental questions can only be answered in the context of appropriate reference systems in which both aspects, space and time, are realized with a sufficiently high level of accuracy. This book addresses all those interested in high-precision reference systems and the various techniques (GPS, Very Long Baseline Interferometry, Satellite Laser Ranging, Lunar Laser Ranging) necessary for their realization, including the production and dissemination of time signals.
Download or read book State Space Modeling of Time Series written by Masanao Aoki and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 324 pages. Available in PDF, EPUB and Kindle. Book excerpt: model's predictive capability? These are some of the questions that need to be answered in proposing any time series model construction method. This book addresses these questions in Part II. Briefly, the covariance matrices between past data and future realizations of time series are used to build a matrix called the Hankel matrix. Information needed for constructing models is extracted from the Hankel matrix. For example, its numerically determined rank will be the di mension of the state model. Thus the model dimension is determined by the data, after balancing several sources of error for such model construction. The covariance matrix of the model forecasting error vector is determined by solving a certain matrix Riccati equation. This matrix is also the covariance matrix of the innovation process which drives the model in generating model forecasts. In these model construction steps, a particular model representation, here referred to as balanced, is used extensively. This mode of model representation facilitates error analysis, such as assessing the error of using a lower dimensional model than that indicated by the rank of the Hankel matrix. The well-known Akaike's canonical correlation method for model construc tion is similar to the one used in this book. There are some important differ ences, however. Akaike uses the normalized Hankel matrix to extract canonical vectors, while the method used in this book does not normalize the Hankel ma trix.
Download or read book Gaussian Markov Random Fields written by Havard Rue and published by CRC Press. This book was released on 2005-02-18 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studie
Download or read book Connecting Quarks with the Cosmos written by National Research Council and published by National Academies Press. This book was released on 2003-03-12 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances made by physicists in understanding matter, space, and time and by astronomers in understanding the universe as a whole have closely intertwined the question being asked about the universe at its two extremesâ€"the very large and the very small. This report identifies 11 key questions that have a good chance to be answered in the next decade. It urges that a new research strategy be created that brings to bear the techniques of both astronomy and sub-atomic physics in a cross-disciplinary way to address these questions. The report presents seven recommendations to facilitate the necessary research and development coordination. These recommendations identify key priorities for future scientific projects critical for realizing these scientific opportunities.
Download or read book The Science of Space time written by Derek J. Raine and published by . This book was released on 1981 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book A Concept of Mathematical Physics written by Tamas Matolcsi and published by . This book was released on 1984 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Exact Space Time Models of Gravitational Waves written by Peter A. Hogan and published by Springer Nature. This book was released on 2022-10-27 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book is about exact space-time models of the gravitational fields produced by gravitational radiation. The authors’ extensive work in the field is reviewed in order to stimulate the study of such models, that have been known for a long time, and to highlight interesting physical aspects of the existing models in some novel detail. There is an underlying simplicity to the gravitational radiation studied in this book. Apart from the basic assumption that the radiation has clearly identifiable wave fronts, the gravitational waves studied are directly analogous to electromagnetic waves. The book is meant for advanced students and researchers who have a knowledge of general relativity sufficient to carry out research in the field.
