| 书目名称 | Spatial Statistics and Computational Methods | | 编辑 | Jesper Møller | | 视频video | | | 丛书名称 | Lecture Notes in Statistics | | 图书封面 |  | | 描述 | Spatial statistics and Markov Chain Monte Carlo (MCMC) techniques have each undergone major developments in the last decade. Also, these two areas are mutually reinforcing, because MCMC methods are often necessary for the practical implementation of spatial statistical inference, while new spatial stochastic models in turn motivate the development of improved MCMC algorithms. This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It consists of four chapters: 1. Petros Dellaportas and Gareth O. Roberts give a tutorial on MCMC methods, the computational methodology which is essential for virtually all the complex spatial models to be considered in subsequent chapters. 2. Peter J. Diggle, Paulo J, Ribeiro Jr., and Ole F. Christensen introduce the reader to the model- based approach to geostatistics, i.e. the application of general statistical principles to the formulation of explicit stochastic models for geostatistical data, and to inference within a declared class of models. 3. Merrilee A. Hurn, Oddvar K. Husby, and H?vard Rue discuss various aspects of image | | 出版日期 | Book 2003 | | 关键词 | computational statistics; geostatistics; statistical inference; statistics | | 版次 | 1 | | doi | https://doi.org/10.1007/978-0-387-21811-3 | | isbn_softcover | 978-0-387-00136-4 | | isbn_ebook | 978-0-387-21811-3Series ISSN 0930-0325 Series E-ISSN 2197-7186 | | issn_series | 0930-0325 | | copyright | Springer Science+Business Media New York 2003 |
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发表于 2025-3-21 19:29:04
