Focusing on Bayesian methods and maximum entropy, this book shows how a few fundamental rules can be used to tackle a variety of problems in data analysis. Topics covered include reliability analysis, multivariate optimisation, least-squares and maximum likelihood, and more.
Bibliography, etc. Note
Includes bibliographical references (pages 237-240) and index.
Formatted Contents Note
PART I: THE ESSENTIALS; 1. The basics; 2. Parameter estimation I; 3. Parameter estimation II; 4. Model selection; 5. Assigning probabilities; PART II: ADVANCED TOPICS; 6. Non-parametric estimation; 7. Experimental design; 8. Least-squares extensions; 9. Nested sampling; 10. Quantification; A. Gaussian integrals; B. Cox's derivation of probability.
Digital File Characteristics
Oxford science publications.
Available in Other Form
Print version: Sivia, D.S. Data analysis. 2nd ed. Oxford ; New York : Oxford University Press, 2006