A state-of-the-art presentation of spatio-temporal processes, bridging classic ideas with modern hierarchical statistical modeling concepts and the latest computational methods 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 Wiklesupply 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.
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這是繼Cressie本人在1993年空間統計領域的里程碑式的著作"Statistics for Spatial Data"後的又一力作。Cressie此牛人自身著作等身，也培养了诸位在空间统计研究中的青年才俊，不乏如Wikle般在環境科學中引入Hierarchical Bayeisan Models的先驅。此書內容可以大致歸納為以下四...
评分這是繼Cressie本人在1993年空間統計領域的里程碑式的著作"Statistics for Spatial Data"後的又一力作。Cressie此牛人自身著作等身，也培养了诸位在空间统计研究中的青年才俊，不乏如Wikle般在環境科學中引入Hierarchical Bayeisan Models的先驅。此書內容可以大致歸納為以下四...
评分這是繼Cressie本人在1993年空間統計領域的里程碑式的著作"Statistics for Spatial Data"後的又一力作。Cressie此牛人自身著作等身，也培养了诸位在空间统计研究中的青年才俊，不乏如Wikle般在環境科學中引入Hierarchical Bayeisan Models的先驅。此書內容可以大致歸納為以下四...
评分這是繼Cressie本人在1993年空間統計領域的里程碑式的著作"Statistics for Spatial Data"後的又一力作。Cressie此牛人自身著作等身，也培养了诸位在空间统计研究中的青年才俊，不乏如Wikle般在環境科學中引入Hierarchical Bayeisan Models的先驅。此書內容可以大致歸納為以下四...
评分這是繼Cressie本人在1993年空間統計領域的里程碑式的著作"Statistics for Spatial Data"後的又一力作。Cressie此牛人自身著作等身，也培养了诸位在空间统计研究中的青年才俊，不乏如Wikle般在環境科學中引入Hierarchical Bayeisan Models的先驅。此書內容可以大致歸納為以下四...
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评分6.3 Statistics for Spatio-Temporal Data 2011.epub
评分6.3 Statistics for Spatio-Temporal Data 2011.epub
评分6.3 Statistics for Spatio-Temporal Data 2011.epub
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