Müller P., Vidakovic B. (eds.) Bayesian Inference in Wavelet-Based Models

New York: Springer, 1999. — 405 p.This volume presents an overview of Bayesian methods for inference in the wavelet domain. The papers in this volume are divided into six parts: The first two papers introduce basic concepts. Chapters in Part II explore different approaches to prior modeling, using independent priors. Papers in the Part III discuss decision theoretic aspects of such prior models. In Part IV, some aspects of prior modeling using priors that account for dependence are explored. Part V considers the use of 2-dimensional wavelet decomposition in spatial modeling. Chapters in Part VI discuss the use of empirical Bayes estimation in wavelet based models. Part VII concludes the volume with a discussion of case studies using wavelet based Bayesian approaches. The cooperation of all contributors in the timely preparation of their manuscripts is greatly recognized. We decided early on that it was impor­ tant to referee and critically evaluate the papers which were submitted for inclusion in this volume. For this substantial task, we relied on the service of numerous referees to whom we are most indebted. We are also grateful to John Kimmel and the Springer-Verlag referees for considering our proposal in a very timely manner. Our special thanks go to our spouses, Gautami and Draga, for their support.An Introduction to Wavelets
Spectral View of Wavelets and Nonlinear Regression
Bayesian Approach to Wavelet Decomposition and Shrinkage
Some Observations on the Tractability of Certain Multi-Scale Models
Bayesian Analysis of Change-Point Models
Prior Elicitation in the Wavelet Domain
Wavelet Nonparametric Regression Using Basis Averaging
An Overview of Wavelet Regularization
Minimax Restoration and Deconvolution
Robust Bayesian and Bayesian Decision Theoretic Wavelet Shrinkage
Best Basis Representations with Prior Statistical Models
Modeling Dependence in the Wavelet Domain
MCMC Methods in Wavelet Shrinkage: Non-Equally Spaced Regression, Density and Spectral Density Estimation
Empirical Bayesian Spatial Prediction Using Wavelets
Geometrical Priors for Noisefree Wavelet Coefficients in Image Denoising
Multiscale Hidden Markov Models for Bayesian Image Analysis
Wavelets for Object Representation and Recognition in Computer Vision
Bayesian Denoising of Visual Images in the Wavelet Domain
Empirical Bayes Estimation in Wavelet Nonparametric Regression
Nonparametric Empirical Bayes Estimation via Wavelets
Multiresolution Wavelet Analyses in Hierarchical Bayesian Turbulence Models
Low Dimensional Turbulent Transport Mechanics Near the Forest-Atmosphere Interface
Latent Structure Analyses of Turbulence Data Using Wavelets and Time Series Decompositions