| 書目名稱 | Multiscale Modeling |
| 副標題 | A Bayesian Perspecti |
| 編輯 | Marco A. R. Ferreira,Herbert K. H. Lee |
| 視頻video | http://file.papertrans.cn/642/641147/641147.mp4 |
| 概述 | Stochastic models for processes that live and can possibly be observed at different levels of resolution.The models in this book allow different degrees of smoothness of the stochastic processes at th |
| 叢書名稱 | Springer Series in Statistics |
| 圖書封面 |  |
| 描述 | .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.. |
| 出版日期 | Book 2007 |
| 關鍵詞 | Monte Carlo; Time series; aggregation; bayesian analysis; bayesian statistics; computed tomography (CT); g |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-70898-0 |
| isbn_softcover | 978-1-4419-2426-1 |
| isbn_ebook | 978-0-387-70898-0Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer-Verlag New York 2007 |
|Archiver|手機版|小黑屋|
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