Publication year: 2007
ISBN: 978-0-387-70898-0
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The book is aimed at statisticians, applied mathematicians, and engineers working on problems dealing with multiscale processes in time and/or space, such as in engineering, finance, and environmetrics. The book will also be of interest to those working on multiscale computation research. The main prerequisites are knowledge of Bayesian statistics and basic Markov chain Monte Carlo methods. A number of real-world examples are thoroughly analyzed in order to demonstrate the methods and to assist the readers in applying these methods to their own work. To further assist readers, the authors are making source code (for R) available for many of the basic methods discussed herein.
Subject: Mathematics and Statistics, Monte Carlo, Time series, aggregation, bayesian analysis, bayesian statistics, computed tomography (CT), geographic data, image analysis, model, modeling, multiresolution modeling, multiscale analysis, statistics