Bayesian theory


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Bayesian theory

[′bāz·ē·ən ‚thē·ə·rē]
(statistics)
A theory, as of statistical inference or decision making, in which probabilities are associated with individual events or statements rather than with sequences of events.
References in periodicals archive ?
Bayesian theory "tells you what they should conclude from those prior beliefs and that evidence.
Based on the Bayesian theory, the probability of the error recognition is [18]
In the Bayesian theory, we know that posterior probability [varies] likelihood x prior probability.
Hawboldt, "Dynamic risk assessment using failure assessment and Bayesian theory," Journal of Loss Prevention in the Process Industries, vol.
In this book, Bayesian theory is discussed from chapter 6 to chapter 9.
This classification algorithm predicts the possibility of a class relation pattern when the prior probability and conditional probability are known, which is based on Bayesian theory of probability statistics.
The discussion of the use of the Bayesian theory continues well into the final section that centers on more existential problems: climate change, terrorism, and the bubbles in financial markets.
Tsokos, Bayesian Theory and Methods, Springer, 2014.
A modest knowledge of probability and statistics is required, they say, in particular readers should know the basic concepts of maximum likelihood estimation and Bayesian theory.
It discusses this analysis using two-dimensional semantics and the Bayesian theory.
The section 'Judgement and Decision-Making' highlights the disagreements among the contributors on whether the proper framework for human cognition should be Bayesian theory, heuristics, or naive statistics, and it considers the assessment of the normative implications of these alternatives.
Clark includes a description of Bayesian theory for comparison and contrast and a number of exercises readers can use to uncover the nature of the models using both classic and new data sets.