Multiscale Modeling
A Bayesian Perspective
Seiten
2010
|
Softcover reprint of hardcover 1st ed. 2007
Springer-Verlag New York Inc.
978-1-4419-2426-1 (ISBN)
Springer-Verlag New York Inc.
978-1-4419-2426-1 (ISBN)
A wide variety of processes occur on multiple scales, either naturally or as a consequence of measurement. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice.
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 audience. Taking a Bayesian approach allows for full accounting of uncertainty, and also addresses the delicate issue of uncertainty at multiple scales. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice.
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 audience. Taking a Bayesian approach allows for full accounting of uncertainty, and also addresses the delicate issue of uncertainty at multiple scales. The Bayesian approach also facilitates the use of knowledge from prior experience or data, and these methods can handle different amounts of prior knowledge at different scales, as often occurs in practice.
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.
| Erscheint lt. Verlag | 19.11.2010 |
|---|---|
| Reihe/Serie | Springer Series in Statistics |
| Zusatzinfo | XII, 245 p. |
| Verlagsort | New York, NY |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Themenwelt | Informatik ► Grafik / Design ► Digitale Bildverarbeitung |
| Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik | |
| Naturwissenschaften ► Geowissenschaften ► Geografie / Kartografie | |
| Wirtschaft ► Volkswirtschaftslehre ► Ökonometrie | |
| ISBN-10 | 1-4419-2426-4 / 1441924264 |
| ISBN-13 | 978-1-4419-2426-1 / 9781441924261 |
| Zustand | Neuware |
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