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DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial

DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial

DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial
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DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial Paperback - 2006 - 2nd Edition

by SIVIA, Devinderjit

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Oxford University Press. 2. Acceptable. The item might be beaten up but readable. May contain markings or highlighting, as well as stains, bent corners, or any other major defect, but the text is not obscured in any way.
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Details

  • Title DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial
  • Author SIVIA, Devinderjit
  • Binding Paperback
  • Edition number 2nd
  • Edition 2
  • Condition Used - Acceptable
  • Pages 264
  • Volumes 1
  • Language ENG
  • Publisher Oxford University Press
  • Publication date 2006-07-27
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index, Table of Contents
  • Bookseller's Inventory # 0198568320-7-1
  • ISBN 9780198568322 / 0198568320
  • Weight 0.91 lbs (0.41 kg)
  • Dimensions 9.14 x 7.56 x 0.57 in (23.22 x 19.20 x 1.45 cm)
  • Category Mathematics
  • Dewey Decimal Code 519.542
  • Quantity available 1

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Reader reviews for DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial

From the publisher

Statistics lectures have been a source of much bewilderment and frustration for generations of students. This book attempts to remedy the situation by expounding a logical and unified approach to the whole subject of data analysis.

This text is intended as a tutorial guide for senior undergraduates and research students in science and engineering. After explaining the basic principles of Bayesian probability theory, their use is illustrated with a variety of examples ranging from elementary parameter estimation to image processing. Other topics covered include reliability analysis, multivariate optimization, least-squares and maximum likelihood, error-propagation, hypothesis testing, maximum entropy and experimental design.

The Second Edition of this successful tutorial book contains a new chapter on extensions to the ubiquitous least-squares procedure, allowing for the straightforward handling of outliers and unknown correlated noise, and a cutting-edge contribution from John Skilling on a novel numerical technique for Bayesian computation called 'nested sampling'.

Media reviews

Citations

  • Scitech Book News, 12/01/2006, Page 33

About the author

Devinderjit Singh Sivia
Rutherford Appleton Laboratory
Chilton
Oxon
OX11 5DJ John Skilling
Maximum Entropy Data Consultants
42 Southgate Street
Bury St Edmonds
Suffolk
IP33 2AZ
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