{"product_id":"9781119243069","title":"Statistics for Spatio-Temporal Data","description":"\u003cb\u003eWinner of the 2013 DeGroot Prize.\u003cbr\u003e \u003cbr\u003e A state-of-the-art presentation of spatio-temporal processes,\u003c\/b\u003e \u003cb\u003ebridging classic ideas with modern hierarchical statistical\u003c\/b\u003e \u003cb\u003emodeling concepts and the latest computational methods\u003c\/b\u003e \u003cp\u003eNoel Cressie and Christopher K. Wikle, are also \u003cb\u003ewinners of the 2011 PROSE Award in the Mathematics category\u003c\/b\u003e, 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.)\u003c\/p\u003e \u003cp\u003e\u003ci\u003eStatistics for Spatio-Temporal Data\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eFrom 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. \u003ci\u003eStatistics for Spatio-Temporal Data\u003c\/i\u003e 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.\u003c\/p\u003e \u003cp\u003eCressie 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.\u003c\/p\u003e \u003cp\u003eTopics of coverage include:\u003c\/p\u003e \u003cul\u003e \u003cli\u003eExploratory methods for spatio-temporal data, including visualization, spectral analysis, empirical orthogonal function analysis, and LISAs\u003c\/li\u003e \u003cli\u003eSpatio-temporal covariance functions, spatio-temporal kriging, and time series of spatial processes\u003c\/li\u003e \u003cli\u003eDevelopment of hierarchical dynamical spatio-temporal models (DSTMs), with discussion of linear and nonlinear DSTMs and computational algorithms for their implementation\u003c\/li\u003e \u003cli\u003eQuantifying and exploring spatio-temporal variability in scientific applications, including case studies based on real-world environmental data\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003eThroughout 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. \u003ci\u003eStatistics for Spatio-Temporal Data\u003c\/i\u003e 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.\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":47078377357552,"sku":"9781119243069","price":73.49,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0737\/7593\/9824\/files\/9781119243069_p0.jpg?v=1763696872","url":"https:\/\/shop-qa.barnesandnoble.com\/products\/9781119243069","provider":"Barnes \u0026 Noble (DEV)","version":"1.0","type":"link"}