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Bayesian Inference in Wavelet-Based Models (Lecture Notes in Statistics)
Peter Müller
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Description for Bayesian Inference in Wavelet-Based Models (Lecture Notes in Statistics)
Paperback. This title links two of the most active areas of statistics, Bayesian statistics and wavelets. Editor(s): Vidakovic, Brani; Muller, P. Series: Lecture Notes in Statistics. Num Pages: 396 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly. Dimension: 235 x 155 x 21. Weight in Grams: 581.
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. ... Read more
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. ... Read more
Product Details
Format
Paperback
Publication date
1999
Publisher
Springer
Condition
New
Series
Lecture Notes in Statistics
Number of Pages
396
Place of Publication
New York, NY, United States
ISBN
9780387988856
SKU
V9780387988856
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
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