Displaying similar documents to “Algorithm. 45. Bayes factor test. An algorithm giving tables for a non-parametric two-sample test of the Bayesian discrimination power of an observed factor”

Hypothesis testing: Discussion.

Edwin T. Jaynes, David J. Spiegelhalter, Hirotugu Akaike, Arthur P. Dempster, James M. Dickey, Seymour Geisser, Irving John Good, Dennis V. Lindley, Anthony O'Hagan, Arnold Zellner (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Zellner, Arnold and Siow, Aloysius, Posterior odds ratios for selected regression hypotheses and by Bernardo, José M., A Bayesian analysis of classical hypotheses testing, both of them part of a round table on Hypothesis testing held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Bayesian and non-Bayesian conditional inference: Discussion.

A. Philip Dawid, Morris H. DeGroot, James M. Dickey, Irving John Good, Bruce M. Hill, Joseph B. Kadane, Tom Leonard, Dennis B. Lindley, Arnold Zellner (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the paper by Barnard, George A., Pivotal inference and the Bayesian controversy, part of a round table on Bayesian and non-Bayesian conditional inference held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

On the frequentist and Bayesian approaches to hypothesis testing.

Elías Moreno, F. Javier Girón (2006)

SORT

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Hypothesis testing is a model selection problem for which the solution proposed by the two main statistical streams of thought, frequentists and Bayesians, substantially differ. One may think that this fact might be due to the prior chosen in the Bayesian analysis and that a convenient prior selection may reconcile both approaches. However, the Bayesian robustness viewpoint has shown that, in general, this is not so and hence a profound disagreement between both approaches exists. In...

Unimodal contaminations in testing point null hypothesis.

Miguel Angel Gómez-Villegas, Luís Sanz (2003)

RACSAM

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The problem of testing a point null hypothesis from the Bayesian perspective is considered. The uncertainties are modelled through use of ε?contamination class with the class of contaminations including: i) All unimodal distributions and ii) All unimodal and symmetric distributions. Over these classes, the infimum of the posterior probability of the point null hypothesis is computed and compared with the p?value and a better approach than the one known is obtained.

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J. de la Horra (2009)

Boletín de Estadística e Investigación Operativa. BEIO

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A Bayesian significance test of change for correlated observations

Abdeldjalil Slama (2014)

Discussiones Mathematicae Probability and Statistics

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This paper presents a Bayesian significance test for a change in mean when observations are not independent. Using a noninformative prior, a unconditional test based on the highest posterior density credible set is determined. From a Gibbs sampler simulation study the effect of correlation on the performance of the Bayesian significance test derived under the assumption of no correlation is examined. This paper is a generalization of earlier studies by KIM (1991) to not independent observations. ...

A Bayesian analysis of classical hypotheses testing.

José M. Bernardo (1980)

Trabajos de Estadística e Investigación Operativa

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The procedure of maximizing the missing information is applied to derive reference posterior probabilities for null hypotheses. The results shed further light on Lindley's paradox and suggest that a Bayesian interpretation of classical hypothesis testing is possible by providing a one-to-one approximate relationship between significance levels and posterior probabilities.