Data Analysis: A Bayesian Tutorial by Devinderjit S. Sivia, John Skilling

Product Details

Synopsis

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'.

Biography

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