This book presents Bayes' theorem, the estimation of unknown parameters, the determination of confidence regions and the derivation of tests of hypotheses for the unknown parameters. It does so in a simple manner that is easy to comprehend. The book compares traditional and Bayesian methods with the rules of probability presented in a logical way allowing an intuitive understanding of random variables and their probability distributions to be formed.
Probability.- Parameter Estimation, Confidence Regions and Hypothesis Testing.- Linear Model.- Special Models and Applications.- Numerical Methods.
From the reviews of the second edition: "This is a well-written introduction to Bayesian Analysis that contains many applications to Geodesy and Engineering at the cutting edge of these topics. ... There is a good treatment of Bayesian Analysis of Linear Models ... . The references are very interesting ... by a group of scientists of whose work many of us in the Statistical profession may not be aware. The strength of the book lies in its coverage, careful mathematics and many contemporary applications." (Jayanta K. Ghosh, International Statistical Review, Vol. 76 (1), 2008)
Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
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INTRO TO BAYESIAN STATISTICS 2
Softcover of Or