Multiscale Modelling : A Bayesian Perspective
A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement. This book contains methodology for the analysis of data that arise from such multiscale processes. The book brings together a number of recent developments and makes them accessible to a wider...
Guardat en:
| Autors principals: | , |
|---|---|
| Format: | Livre numérique |
| Idioma: | Anglais |
| Publicat: |
New York, NY :
Springer New York
[20..].
Cham : Springer Nature |
| Edició: | 1st ed. 2007. |
| Col·lecció: | Springer Series in Statistics
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| Matèries: | |
| Accés en línia: | Accès sur la plateforme de l'éditeur Accès sur la plateforme Istex Accès Université d'Orléans Accès INSA CVL |
| Nota: |
L'impression du document génère 239 p. Archives Springer e-books (Licence nationale) Archives Springer e-books (Licence nationale) |
| Autres localisations: | Voir dans le Sudoc |
| Edition sous un autre format: | • Multiscale modeling, a Bayesian perspective, Marco A.R. Ferreira, Herbert K.H. Lee, 2007, New York, Springer, 1 volume (XII-245 pages), Springer series in statistics, 978-0-387-70897-3 |
Taula de continguts:
- Models for Spatial Data Illustrative Example Convolutions and Wavelets Convolution Methods Wavelet Methods Explicit Multiscale Models Overview of Explicit Multiscale Models Gaussian Multiscale Models on Trees Hidden Markov Models on Trees Mass-Balanced Multiscale Models on Trees Multiscale Random Fields Multiscale Time Series Change of Support Models Implicit Multiscale Models Implicit Computationally Linked Model Overview Metropolis-Coupled Methods Genetic Algorithms Case Studies Soil Permeability Estimation Single Photon Emission Computed Tomography Example Conclusions.