Displaying similar documents to “Hypothesis testing: Discussion.”

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...

Likelihood, sufficiency and ancillarity: Discussion.

George A. Barnard, P. R. Freeman, Daniel Peña, James M. Dickey, Seymour Geisser, Dennis V. Lindley, Anthony O'Hagan, Adrian F. M. Smith (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Akaike, Hirotugu, Likelihood and the Bayes procedure and by Dawid, A. Philip, A Bayesian look at nuisance parameters, both of them part of a round table on Likelihood, sufficiency and ancillarity held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

Coherence of models and utilities: Discussion.

James M. Dickey, William H. DuMouchel, José M. Bernardo, Simon French, Joseph B. Kadane, Dennis V. Lindley, Anthony O'Hagan, Adrian F. M. Smith, Thomas W. F. Stroud (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Leonard, Tom, The roles of inductive modelling and coherence in Bayesian statistics and by Novick, Melvin R., Dekeyrel, D.F. and Chuang, D.T., Local and regional coherence utility assessment procedures, both of them part of a round table on Coherence of models and utilities held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

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.

Some history of the hierarchical Bayesian methodology.

Irving John Good (1980)

Trabajos de Estadística e Investigación Operativa

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A standard tecnique in subjective Bayesian methodology is for a subject (you) to make judgements of the probabilities that a physical probability lies in various intervals. In the Bayesian hierarchical technique you make probability judgements (of a higher type, order, level or stage) concerning the judgements of lower type. The paper will outline some of the history of this hierarchical technique with emphasis on the contributions by I. J. Good because I have read every word written...

Predictive sample reuse: Discussion.

Irwin Guttman, S. James Press (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the paper by Geisser, Seymour, Predictive sample reuse techniques for censored data, 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 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? ...