Mathematical Modeling of Random and Deterministic Phenomena
Mathematical Modeling of Random and Deterministic Phenomena

Author: Solym Mawaki Manou-Abi

Publisher: John Wiley & Sons

Published: 2020-04-28

Total Pages: 308

ISBN-13: 1786304546

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This book highlights mathematical research interests that appear in real life, such as the study and modeling of random and deterministic phenomena. As such, it provides current research in mathematics, with applications in biological and environmental sciences, ecology, epidemiology and social perspectives. The chapters can be read independently of each other, with dedicated references specific to each chapter. The book is organized in two main parts. The first is devoted to some advanced mathematical problems regarding epidemic models; predictions of biomass; space-time modeling of extreme rainfall; modeling with the piecewise deterministic Markov process; optimal control problems; evolution equations in a periodic environment; and the analysis of the heat equation. The second is devoted to a modelization with interdisciplinarity in ecological, socio-economic, epistemological, demographic and social problems. Mathematical Modeling of Random and Deterministic Phenomena is aimed at expert readers, young researchers, plus graduate and advanced undergraduate students who are interested in probability, statistics, modeling and mathematical analysis.

Spatiotemporal Random Fields
Spatiotemporal Random Fields

Author: George Christakos

Publisher: Elsevier

Published: 2017-07-26

Total Pages: 698

ISBN-13: 0128030321

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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

Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA
Advanced Spatial Modeling with Stochastic Partial Differential Equations Using R and INLA

Author: Elias T. Krainski

Publisher: CRC Press

Published: 2018-12-07

Total Pages: 284

ISBN-13: 0429629850

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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.

Rainfall
Rainfall

Author: Renato Morbidelli

Publisher: Elsevier

Published: 2022-02-11

Total Pages: 502

ISBN-13: 0128225440

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Rainfall: Physical Process, Measurement, Data Analysis and Usage in Hydrological Investigations integrates different rainfall perspectives, from droplet formation and modeling developments to the experimental measurements and their analysis, to application in surface and subsurface hydrological investigations. Each chapter provides an updated representation of the involved subject with relative open problems and includes a case study at the end of the chapter. The book targets postgraduate readers studying meteorology, civil and environmental engineering, geophysics, agronomy and natural science, as well as practitioners working in the fields of hydrology, hydrogeology, agronomy and water resource management. Presents comprehensive coverage of rainfall-related topics, from the basic processes involved in the drop formation to data use and modeling Provides real-life examples for practical use in the form of a case study in each chapter

Rainfall - Runoff Modelling
Rainfall - Runoff Modelling

Author: Keith J. Beven

Publisher: John Wiley & Sons

Published: 2003

Total Pages: 384

ISBN-13: 9780470866719

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Amid climatic changes linked to global warming, ongoing changes in land-use patterns, and growing international concern with the environment it is increasingly important to understand the potential impact of these changes on the environment. Rainfall-runoff modeling is an important predictor of that impact. This book introduces rainfall-runoff models that have been developed over the past 24-30 years, giving examples of their practical applications. It provides a summary of available techniques for rainfall modeling based upon the most recent research, but in a way that serves as a primer for the subject. Provides an overview of how catchment rainfall-runoff systems work A history of rainfall-runoff models Examples of models can be downloaded over the Internet Looks at uncertainty in model prediction