Bayesian Inference in Wavelet Based Models
Contributors: Peter Müller (Editor); Brani Vidakovic (Editor)
Publisher: Springer
Published: June 22, 1999
Language: eng
Number of pages: 394
ISBN-13: 9780387988856
Description: "This volume provides a thorough introduction and reference for any researcher who is interested in Bayesian inference for wavelet-based models. 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."--BOOK JACKET.