| 书目名称 | Spatial Statistics and Modeling | | 编辑 | Carlo Gaetan,Xavier Guyon | | 视频video | http://file.papertrans.cn/874/873571/873571.mp4 | | 概述 | Clear and precise presentation of the most important spatial models, including their probabilistic properties and related statistical methods.Implements these models and studies their statistics on a | | 丛书名称 | Springer Series in Statistics | | 图书封面 |  | | 描述 | .Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete... The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation)..A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and | | 出版日期 | Book 2010 | | 关键词 | Applied statistics; Geostatistics; Markov random field; Point process; Spatial statistics and modeling; a | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-92257-7 | | isbn_softcover | 978-1-4614-2499-4 | | isbn_ebook | 978-0-387-92257-7Series ISSN 0172-7397 Series E-ISSN 2197-568X | | issn_series | 0172-7397 | | copyright | Springer-Verlag New York 2010 |
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