Hierarchical Modeling and Analysis for Spatial Data

Hierarchical Modeling and Analysis for Spatial Data is the first accessible, up-to-date treatment of Bayesian methods, modeling, and data analysis for spatial and spatio-temporal data. Self-contained, it includes overviews of the necessary background material, exercises, and brief tutorial on using WinBUGS, R, and S-Plus software for Bayesian modeling. This book provides clear explanations, plentiful illustrations--some in full color--and lays the groundwork for using easily accessible software to immediately apply the techniques to your data. Written by a team of real leaders in the field, it will undoubtedly remain the primary textbook and reference on the subject for years to come.

Table des matières

Overview of Spatial Data Problems. Basics of Point-Referenced Data Models. Basics of Areal Data Models. Basics of Bayesian Inference. Hierarchical Modeling for Univariate Spatial Data. Spatial Misalignment. Multivariate Spatial Modeling. Spatio-temporal Modeling. Spatial Survival Models. Special Topics in Spatial Process Modeling. Appendices: References . Author Index. Subject Index

Détails du produit

• Auteurs: Sudipto Banerjee, Sudipto Gelfand Banerjee, Bradley P. Carlin, Alan E. Gelfrand
• Edition: Taylor & Francis Ltd.
• Langues: Anglais, Espagnol
• Format d'édition: Livre Relié
• Sortie: 17.12.2003
• EAN: 9781584884101
• ISBN: 978-1-58488-410-1
• Pages: 472
• Catégorie: Sciences naturelles, médecine, informatique, technique > Mathématiques > Général, dictionnaires