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Data Analysis

A Bayesian Tutorial. For Scientists and Engineers

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 imageprocessing. 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 techniquefor Bayesian computation called 'nested sampling'.
Portrait

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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Einband Taschenbuch
Seitenzahl 189
Erscheinungsdatum 01.06.2006
Sprache Englisch
ISBN 978-0-19-856832-2
Verlag Oxford University Press
Maße (L/B/H) 238/158/20 mm
Gewicht 429
Auflage 2Rev ed.
Buch (Taschenbuch, Englisch)
36,99
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