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Data Analysis
Devinderjit Sivia
John Skilling
其他書名
A Bayesian Tutorial
出版
Oxford University Press
, 2006-06
主題
Mathematics / Applied
Mathematics / Probability & Statistics / General
Mathematics / Probability & Statistics / Bayesian Analysis
Science / General
Science / Life Sciences / Botany
Science / Physics / General
Technology & Engineering / Engineering (General)
ISBN
0198568312
9780198568315
URL
http://books.google.com.hk/books?id=lYMSDAAAQBAJ&hl=&source=gbs_api
EBook
SAMPLE
註釋
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'.