Principles of Uncertainty

Principles of Uncertainty

Principles of Uncertainty, by Joseph B. Kadane, is a well-written and comprehensive introduction to theory of Bayesian statistics.


An intuitive and mathematical introduction to subjective probability and Bayesian statistics. An accessible, comprehensive guide to the theory of Bayesian statistics, Principles of Uncertainty presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.

Table of Contents

  • Probability
  • Conditional Probability and Bayes Theorem
  • Discrete Random Variables
  • Continuous Random Variables
  • Transformations
  • Characteristic Functions, the Normal Distribution and the Central Limit Theorem
  • Making Decisions
  • Conjugate Analysis
  • Hierarchical Structuring of a Model
  • Bayesian Computation: Markov Chain Monte Carlo
  • Multiparty Problems
  • Exploration of Old Ideas

Book Details

Author(s): Joseph B. Kadane
Publisher: CRC Press
Format(s): PDF
File size: 2.82 MB
Number of pages: 499
Link: Principles of Uncertainty [PDF]

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