Spatiotemporal Stochastic Processes PDF Download
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Author: Geoffrey S. Waston
Publisher:
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
The principal investigator's with Accardi on coherent chains is described in Accardi's survey of his research. However, the area where Watson mainly worked with Accardi on the possibilities of a theory of statistics based on quantum probability is not described. Despite an enormous investment of time and effort, and several drafts of papers, this research was abandoned because it did not interest physicists or statistical audiences at talks. This lead to the construction of interesting (classical) Markov motions on the sphere - published in a paper with Accardi and Cabrera. Watson's other papers were also concerned with distributions and inference on spheres. Mardia's work was motivated by pattern analysis, and used Fuzzy set theory. This work was closet to the original goal of the contract.
Author: Geoffrey S. Waston
Publisher:
ISBN:
Category :
Languages : en
Pages : 7
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Book Description
The principal investigator's with Accardi on coherent chains is described in Accardi's survey of his research. However, the area where Watson mainly worked with Accardi on the possibilities of a theory of statistics based on quantum probability is not described. Despite an enormous investment of time and effort, and several drafts of papers, this research was abandoned because it did not interest physicists or statistical audiences at talks. This lead to the construction of interesting (classical) Markov motions on the sphere - published in a paper with Accardi and Cabrera. Watson's other papers were also concerned with distributions and inference on spheres. Mardia's work was motivated by pattern analysis, and used Fuzzy set theory. This work was closet to the original goal of the contract.
Author: K. S. Alexander
Publisher:
ISBN: 9781461204527
Category :
Languages : en
Pages : 280
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Book Description
Author: Elias T. Krainski
Publisher: CRC Press
ISBN: 0429629850
Category : Mathematics
Languages : en
Pages : 284
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Book Description
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.
Author: Rinaldo B. Schinazi
Publisher:
ISBN: 9783764340810
Category : Stochastic processes
Languages : en
Pages : 178
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Book Description
Author: Silvia Bozza
Publisher:
ISBN:
Category :
Languages : en
Pages : 119
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Book Description
Author: Ruslan K. Chornei
Publisher: Springer Science & Business Media
ISBN: 038731279X
Category : Mathematics
Languages : en
Pages : 269
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Book Description
This book is devoted to the study and optimization of spatiotemporal stochastic processes - processes which develop simultaneously in space and time under random influences. These processes are seen to occur almost everywhere when studying the global behavior of complex systems. The book presents problems and content not considered in other books on controlled Markov processes, especially regarding controlled Markov fields on graphs.
Author: Noel Cressie
Publisher: John Wiley & Sons
ISBN: 1119243041
Category : Mathematics
Languages : en
Pages : 612
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Book Description
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: Jorge Mateu Mahiques
Publisher: Netbiblo
ISBN: 849745412X
Category : Social Science
Languages : en
Pages : 90
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Book Description
This monograph presents a general methodology which is shown to be valid in the analysis of spatial point structures and that is certainly easier to use by non-expert researchers coming from other applied sciences than other much modern techniques. We suggest that the local conditioning approach has the advantage that it is statistically efficient, easy to correct for edge-effects and provides similar results than other (more complicated) likelihood-based methods. We show a mathematical justification to prove that any purely inhibitory pairwise interaction point process (pipp) can be obtained as the limit of a sequence of auto-Poisson lattice schemes and within this context we develop the pseudolikelihood estimating equations. We particularly focus on developing a Monte Carlo simulation study to analyze the behaviour of the parameter s of a particular pipp model derived using this technique. We also stress that this methodology has a wide range of applications in many fields, particularly in economy and demography.
Author: Noel Cressie
Publisher: John Wiley & Sons
ISBN: 1119243068
Category : Mathematics
Languages : en
Pages : 596
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Book Description
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: Ole Barndorff-Nielsen
Publisher:
ISBN:
Category :
Languages : en
Pages :
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Book Description
