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Bayesian Inference in Wavelet-Based Models : Lecture Notes in Statistics - Brani Vidakovic

Bayesian Inference in Wavelet-Based Models

Lecture Notes in Statistics

By: Brani Vidakovic (Editor), P. Muller (Editor)

Paperback Published: 22nd June 1999
ISBN: 9780387988856
Number Of Pages: 396

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This volume provides a thorough introduction and reference for any researcher who is interested in Bayesian inference for wavelet-based models, but is not necessarily an expert in either. To achieve this goal the book starts with an extensive introductory chapter providing a self-contained introduction to the use of wavelet decompositions and the relation to Bayesian inference. The remaining papers in this volume are divided into six parts: independent prior modeling; decision theoretic aspects; dependent prior modeling; spatial models using bivariate wavelet bases; empirical Bayes approaches; and case studies. Chapters are written by experts who published the original research papers establishing the use of wavelet-based models in Bayesian inference. Peter MA1/4ller is Associate Professor and Brani Vidakovic is Assistant Professor of Statistics at Duke University.

Introduction
An Introduction to Waveletsp. 1
Spectral View of Wavelets and Nonlinear Regressionp. 19
Prior Models - Independent Case
Bayesian Approach to Wavelet Decomposition and Shrinkagep. 33
Some Observations on the Tractability of Certain Multi-Scale Modelsp. 51
Bayesian Analysis of Change-Point Modelsp. 67
Prior Elicitation in the Wavelet Domainp. 83
Wavelet Nonparametric Regression Using Basis Averagingp. 95
Decision Theoretic Wavelet Shrinkage
An Overview of Wavelet Regularizationp. 109
Minimax Restoration and Deconvolutionp. 115
Robust Bayesian and Bayesian Decision Theoretic Wavelet Shrinkagep. 139
Best Basis Representations with Prior Statistical Modelsp. 155
Prior Models - Dependent Case
Modeling Dependence in the Wavelet Domainp. 173
MCMC Methods in Wavelet Shrinkagep. 187
Spatial Models
Empirical Bayesian Spatial Prediction Using Waveletsp. 203
Geometrical Priors for Noisefree Wavelet Coefficients in Image Denoisingp. 223
Multiscale Hidden Markov Models for Bayesian Image Analysisp. 243
Wavelets for Object Representation and Recognition in Computer Visionp. 267
Bayesian Denoising of Visual Images in the Wavelet Domainp. 291
Empirical Bayes
Empirical Bayes Estimation in Wavelet Nonparametric Regressionp. 309
Nonparametric Empirical Bayes Estimation via Waveletsp. 323
Case Studies
Multiresolution Wavelet Analyses in Hierarchical Bayesian Turbulence Modelsp. 341
Low Dimensional Turbulent Transport Mechanics Near the Forest-Atmosphere Interfacep. 361
Latent Structure Analyses of Turbulence Data Using Wavelets and Time Series Decompositionsp. 381
Table of Contents provided by Blackwell. All Rights Reserved.

ISBN: 9780387988856
ISBN-10: 0387988858
Series: Lecture Notes in Statistics
Audience: General
Format: Paperback
Language: English
Number Of Pages: 396
Published: 22nd June 1999
Publisher: Springer-Verlag New York Inc.
Country of Publication: US
Dimensions (cm): 23.39 x 15.6  x 2.16
Weight (kg): 0.58