| Document Type
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BL
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| Record Number
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654938
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| Doc. No
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dltt
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| Title & Author
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Spatial statistics and computational methods /\ Jesper Møller (editor).
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| Publication Statement
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New York :: Springer,, 2003.
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| Series Statement
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Lecture notes in statistics ;; 173
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| Page. NO
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xiv, 202 p. :: ill. ;; 24 cm.
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| ISBN
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0387001360 (pbk. : acid-free paper)
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: 9780387001364 (pbk. : acid-free paper)
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| Bibliographies/Indexes
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Includes bibliographical references and index.
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| Contents
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1. An Introduction to MCMC -- 1.1. MCMC and spatial statistics -- 1.2. The Gibbs sampler -- 1.3. The Metropolis-Hastings algorithm -- 1.4. MCMC Theory -- 1.5. Practical implementation -- 1.6. An illustrative example -- 1.7. Appendix: Model determination using MCMC -- 2. An Introduction to Model-Based Geostatistics -- 2.1. Introduction -- 2.2. Examples of geostatistical problems -- 2.3. The general geostatistical model -- 2.4. The Gaussian Model -- 2.5. Parametric estimation of covariance structure -- 2.6. Plug-in prediction -- 2.7. Bayesian inference for the linear Gaussian model -- 2.8. A Case Study: the Swiss rainfall data -- 2.9. Generalised linear spatial models -- 2.10. Discussion -- 2.11. Software
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| Abstract
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"The volume introduces topics of current interest in spatial and computational statistics, which should be accessible and of interest to postgraduate students as well as to experienced statistical researchers. It is partly based on the course material for the "TMR and MaPhySto Summer School on Spatial Statistics and Computational Methods," held at Aalborg University, Denmark, August 19 to 22, 2001."--BOOK JACKET.
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| Subject
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Geography-- Statistical methods.
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| Subject
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Spatial analysis (Statistics)
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| LC Classification
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G70.3.S57 2002
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| Added Entry
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Møller, Jesper.
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