Bayesian Inference in Wavelet-Based Models

I Introduction.- 1 An Introduction to Wavelets.- 2 Spectral View of Wavelets and Nonlinear Regression.- II Prior Models - Independent Case.- 3 Bayesian Approach to Wavelet Decomposition and Shrinkage.- 4 Some Observations on the Iractability of Certain Multi-Scale Models..- 5 Bayesian Analysis of Change-Point Models.- 6 Prior Elicitation in the Wavelet Domain.- 7 Wavelet Nonparametric Regression Using Basis Averaging.- III Decision Theoretic Wavelet Shrinkage.- 8 An Overview of Wavelet Regularization.- 9 Minimax Restoration and Deconvolution.- 10 Robust Bayesian and Bayesian Decision Theoretic Wavelet Shrinkage.- 11 Best Basis Representations with Prior Statistical Models.- IV Prior Models Dependent Case.- 12 Modeling Dependence in the Wavelet Domain.- 13 MCMC Methods in Wavelet Shrinkage.- V Spatial Models.- 14 Empirical Bayesian Spatial Prediction Using Wavelets.- 15 Geometrical Priors for Noisefree Wavelet Coefficients in Image Denoising.- 16 Multiscale Hidden Markov Models for Bayesian Image Analysis.- 17 Wavelets for Object Representation and Recognition in Computer Vision.- 18 Bayesian Denoising of Visual Images in the Wavelet Domain.- VI Empirical Bayes.- 19 Empirical Bayes Estimation in Wavelet Nonparametric Regression.- 20 Nonparametric Empirical Bayes Estimation via Wavelets.- VII Case Studies.- 21 Multiresolution Wavelet Analyses in Hierarchical Bayesian Turbulence Models.- 22 Low Dimensional Turbulent Transport Mechanics Near the Forest-Atmosphere Interface.- 23 Latent Structure Analyses of Turbulence Data Using Wavelets and Time Series Decompositions.