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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.
| Autorius: | Herbert K. H. Lee, Marco A. R. Ferreira, |
| Serija: | Springer Series in Statistics |
| Leidėjas: | Springer US |
| Išleidimo metai: | 2007 |
| Knygos puslapių skaičius: | 260 |
| ISBN-10: | 0387708979 |
| ISBN-13: | 9780387708973 |
| Formatas: | 241 x 160 x 20 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Multiscale Modeling: A Bayesian Perspective“
