Data Analysis: A Bayesian Tutorial

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. 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 -- A. Gaussian Integrals -- B. Cox's Derivation Of Probability. D.s. Sivia With J. Skilling. Previous Ed.: 1996. Includes Bibliographical References (p. [237]-240) And Index.