Displaying similar documents to “Posterior odds ratios for selected regression hypotheses.”

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...

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).

The roles of inductive modelling and coherence in Bayesian statistics.

Tom Leonard (1980)

Trabajos de Estadística e Investigación Operativa

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The role of the inductive modelling process (IMP) seems to be of practical importance in Bayesian statistics; it is recommended that the statistician should emphasize meaningful real-life considerations rather than more formal aspects such as the axioms of coherence. It is argued that whilst axiomatics provide some motivation for the Bayesian philosophy, the real strength of Bayesianism lies in its practical advantages and its plausible representation of real-life processes. A number...

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).

Misclassified multinomial data: a Bayesian approach.

Carlos Javier Pérez, F. Javier Girón, Jacinto Martín, Manuel Ruiz, Carlos Rojano (2007)

RACSAM

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In this paper, the problem of inference with misclassified multinomial data is addressed. Over the last years there has been a significant upsurge of interest in the development of Bayesian methods to make inferences with misclassified data. The wide range of applications for several sampling schemes and the importance of including initial information make Bayesian analysis an essential tool to be used in this context. A review of the existing literature followed by a methodological...

On not being rational.

I. Richard Savage (1980)

Trabajos de Estadística e Investigación Operativa

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A Bayesian decision-theoretic approach appears to me as a sensible idealization of a guide to behaviour. At the same time i would like to understand why my behaviour is not always of this form: I sometimes use randomization and I sometimes find confidence intervals acceptable. Not all of my problems have an explicit cost function. Am I lazy or irrational? Do I use non-Bayesian conventions to help communicate? Is the cost of rationality-computation missing from the Bayesian model? ...