Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

Check order status

Become part of a community of book lovers from all over the world and get access to a whole bunch of benefits. Create an account for free

Free delivery for purchases over 19 990 Ft

DPD point 990 Ft DPD courier 1 190 Ft GLS point 1 190 Ft Hungarian Post 1 795 Ft Hungarian Post 1 690 Ft Hungarian Post 1 690 Ft FoxPost 1 190 Ft Packeta point 1 190 Ft GLS courier 1 690 Ft

Contact

How to shop

Help

My account

▸ Empty :-(

Free shipping on orders over 19,990 Ft via Packeta, Fox Post Box, and DPD Collection Point

Bayesian Inference in Wavelet-Based Models

Name: Bayesian Inference in Wavelet-Based Models
Brand: Springer-Verlag New York Inc.
SKU: 04067086
Price: 39520 HUF
Availability: InStock
Author: Peter
ISBN: 9780387988856

Peter

Miller

Language

English

Book Paperback

Libristo code: 04067086

Publishers Springer-Verlag New York Inc., June 1999

This volume provides a thorough introduction and reference for any researcher who is interested in B... Full description

Libristo code: 04067086

271 b

39 520 Ft

In stock at our supplier Shipping in 5-8 days

Up to 30 days for returns

Customers also purchased

UN FINDE EN GRANADA Villena

Paperback

7 911 Ft

Praktikum Pr parative Organische Chemie Reinhard Brückner

Paperback

21 760 Ft

Végigélni Peter Attia

Hardback

7 111 Ft

PROJECTE 3.16, DESTRESES BASIQUES, RESOLUCIO DE PROBLEMES, MATEMATIQUES, 3 ESO EQUIP EDITORIAL CRUILLA

Book

6 802 Ft

La Chafouitrie Rabah DJOUAMA

Paperback

7 138 Ft

La Casa de la Eficacia: Como Sentar las Bases de la Productividad Personal y Organizacional Pablo Maella Cerillo

Paperback

6 070 Ft

Los oscuros ecos del pasado

Paperback

8 229 Ft

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.