Data analysis : a Bayesian tutorial
- Responsibility
- D.S. Sivia with J. Skilling.
- Language
- English.
- Edition
- [2nd ed.]
- Imprint
- Oxford ; New York : Oxford University Press, 2006.
- Physical description
- xii, 246 p. : ill. ; 24 cm.
- Series
- Oxford science publications.
Access
Available online
- site.ebrary.com ebrary
Math & Statistics Library
Stacks
| Call number | Status |
|---|---|
| QA279.5 .S55 2006 |
SAL3 (off-campus storage)
Stacks
Request
| Call number | Status |
|---|---|
| QA279.5 .S55 2006 |
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Creators/Contributors
- Author/Creator
- Sivia, D. S.
- Contributor
- Skilling, J. (John)
Contents/Summary
- Bibliography
- Includes bibliographical references (p. [237]-240) and index.
- Contents
-
- 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.
- (source: Nielsen Book Data)9780198568315 20160528
- Publisher's Summary
- 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 optimisation, 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'.
(source: Nielsen Book Data)9780198568315 20160528 - Supplemental links
-
Table of contents only
Contributor biographical information
Publisher description
Subjects
Bibliographic information
- Publication date
- 2006
- Series
- Oxford science publications.
- ISBN
- 9780198568315 (hbk.)
- 0198568312 (hbk.)
- 9780198568322 (pbk.)
- 0198568320 (pbk.)
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