R. A. Fisher on Bayes and Bayes' theorem

R. A. Fisher's Fiducial Argument and Bayes' Theorem

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A rough set view on Bayes' theorem

Rough set theory offers new perspective on Bayes’ theorem. The look on Bayes’ theorem offered by rough set theory reveals that any data set (decision table) satisfies the total probability theorem and Bayes’ theorem. These properties can be used directly to draw conclusions from objective data without referring to subjective prior knowledge and its revision if new evidence is available. Thus, t...

General Testing Fisher , Neyman , Pearson , and Bayes

One of the famous controversies in statistics is the dispute between Fisher and Neyman-Pearson about the proper way to conduct a test. Hubbard and Bayarri (2003) gave an excellent account of the issues involved in the controversy. Another famous controversy is between Fisher and almost all Bayesians. Fisher (1956) discussed one side of these controversies. Berger’s Fisher lecture attempted to c...

Discrete Bayes with R

Bayes, E-Bayes and Robust Bayes Premium Estimation and Prediction under the Squared Log Error Loss Function

In risk analysis based on Bayesian framework, premium calculation requires specification of a prior distribution for the risk parameter in the heterogeneous portfolio. When the prior knowledge is vague, the E-Bayesian and robust Bayesian analysis can be used to handle the uncertainty in specifying the prior distribution by considering a class of priors instead of a single prior. In th...