Accuracy,confidence and consensus in bayesian hypothesis inference |
| |
Authors: | Roger J. Owenα |
| |
Affiliation: | Department of Statistics , University College of Wale , Aberystwyth, Dyfed, SY23 3D, UK |
| |
Abstract: | Interest centres on a group of statisticians , each supplied with the same n sample datapoint sandmaking formal Bayesian inference with a common likelihood function but differing prior knowledge and utility functions. Definitions are proposed which quantify, in a commensurable way, the inference processes of “accuracy”, “confidence” and “consensus” for the case of hypothesis inference with a fixed sample size n. The general significance of comparing the three quantifiers is considered. As n increases the asymptotic behaviour of the quantifiers is evaluated and it is found that the three rates of convergence are of the same order as a function of n. The results are interpreted and some of their implications are discussed. |
| |
Keywords: | decision making merging of subjective belief agreement of experts rate of learning decisiveness.α |
|
|