TY  - BOOK
AU  - Sivia, Devinderjit
AU  - Skilling, John
TI  - Data analysis: : a bayesian tutorial
SN  - 9780198568322
PY  - 2006///
CY  - Oxford, U.K.
PB  - Oxford University Press
N1  - 1:The Basics,
2:Parameter Estimation I, 
3:Parameter Estimation II, 
4:Model Selection, 
5:Assigning Probabilities, 
6:Non-parametric Estimation, 
7:Experimental Design, 
8:Least-Squares Extensions, 
9:Nested Sampling, 
10:Quantification, 
Appendices
Bibliography
N2  - 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'
ER  -