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Book Description
The Introduction to Bayesian Statistics (2nd Edition) presents Bayes theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters, in a manner that is simple, intuitive and easy to comprehend. The methods are applied to linear models, in models for a robust estimation, for prediction and filtering and in models for estimating variance components and covariance components. Regularization of inverse problems and pattern recognition are also covered while Bayesian networks serve for reaching decisions in systems with uncertainties. If analytical solutions cannot be derived, numerical algorithms are presented such as the Monte Carlo integration and Markov Chain Monte Carlo methods.
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Product Details
Hardcover: 250 pages
Publisher: Springer; 2nd, updated and enlarged ed. edition (September 10, 2007)
Language: English
ISBN-10: 354072723X
ISBN-13: 978-3540727231
Product Dimensions: 9.4 x 6.2 x 0.7 inches
Shipping Weight: 1.2 pounds (View shipping rates and policies)
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Amazon.com Sales Rank: #1,740,383 in Books (See Bestsellers in Books)
(Publishers and authors: Improve Your Sales)
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