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Detalles bibliogr�ficos

T�tulo: Data Analysis: A Bayesian Tutorial
Editor: Oxford University Press
Fecha de publicaci�n: 2006
Idioma: Ingl�s
ISBN 10: 0198568320
ISBN 13: 9780198568322
Encuadernaci�n: Paperback
Edici�n: 2� Edici�n
Estado: Good

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Sinopsis

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'.

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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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