Bayesian methods are growing more and more popular, finding new practical applications in the fields of health sciences, engineering, environmental sciences, business and economics and social sciences, among others. This book explores the use of Bayesian analysis in the statistical estimation of the unknown phenomenon of interest. The contents demonstrate that where such methods are applicable, they offer the best possible estimate of the unknown. Beyond presenting Bayesian theory and methods of analysis, the text is illustrated with a variety of applications to real world problems.
Author(s): Vladimir Savchuk, Chris P. Tsokos (auth.)
Series: Atlantis Studies in Probability and Statistics 1
Edition: 1
Publisher: Atlantis Press
Year: 2011
Language: English
Pages: 318
Tags: Statistical Theory and Methods; Applications of Mathematics; Mathematical Modeling and Industrial Mathematics; Probability and Statistics in Computer Science; Biostatistics; Popular Science in Mathematics/Computer Science/Natural Science
Front Matter....Pages i-xiv
General Questions of Bayes Theory....Pages 1-15
The Accepted Bayes Method of Estimation....Pages 17-46
The Methods of Parametric Bayes Estimation Based on Censored Samples....Pages 47-77
Nonparametric Bayes Estimation....Pages 79-121
Quasi-Parametric Bayes Estimates of the TTF Probability....Pages 123-162
Estimates of the TTF Probability under the Conditions of a Partial Prior Uncertainty....Pages 163-191
Empirical Bayes Estimates of Reliability....Pages 193-218
Theoretical Model for Engineering Reliability....Pages 219-246
Statistical Reliability Analysis Prior Bayes Estimates....Pages 247-276
Statistical Reliability Analysis Posterior Bayes Estimates....Pages 277-306
Back Matter....Pages 307-317
