DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial
SIVIA, Devinderjit
ISBN 10: 0198568320 ISBN 13: 9780198568322
Published by Oxford University Press, 2006
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About this Item
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***Please Read*** No marks on text - My shelf location 2-C-4*. Seller Inventory # 260318004
Synopsis:
This is the second edition of the first tutorial book on Bayesian methods and maximum entropy aimed at senior undergraduates in science and engineering.
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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Bibliographic Details
Title: DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A ...
Publisher: Oxford University Press
Publication Date: 2006
Binding: paperback
Condition: As New
Edition: 2nd Edition
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Data Analysis: A Bayesian Tutorial
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DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial
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ISBN 13: 9780198568322
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DATA ANALYSISBAYESIAN TUTORIAL
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DATA ANALYSIS:BAYESIAN TUTORIAL 2E PAPER: A Bayesian Tutorial
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Oxford University Press, 2006
ISBN 10: 0198568320
ISBN 13: 9780198568322
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Data Analysis: A Bayesian Tutorial
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Data Analysis : A Bayesian Tutorial
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Data Analysis : A Bayesian Tutorial
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Paperback. Condition: New. 2nd. 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'. Seller Inventory # LU-9780198568322
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