Displaying similar documents to “Quasi-Bayesian behaviour: a more realistic approach to decision making?”

Foundations of subjective probability and decision making: Discussion.

Irving John Good, Ludovico Piccinato, Cesáreo Villegas, James M. Dickey, Morris H. DeGroot, Donald A. S. Fraser, Simon French, Dennis V. Lindley (1980)

Trabajos de Estadística e Investigación Operativa

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Discussion on the papers by Girón, F. J. and Ríos, S., Quasi-Bayesian behaviour: a more realistic approach to dicision making? and by Hill, B. M., On finite additivity, non-conglomerability and statistical paradoxes, both of them part of a round table on Foundations of Subjective Probability and Decision Making held in the First International Congress on Bayesian Methods (Valencia, Spain, 28 May - 2 June 1979).

On the foundations of statistics and decision theory.

José M. Bernardo, Javier Girón (1983)

Trabajos de Estadística e Investigación Operativa

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An elementary axiomatic foundation for decision theory is presented at a general enough level to cover standard applications of Bayesian methods. The intuitive meaning of both axioms and results is stressed. It is argued that statistical inference is a particular decision problem to which the axiomatic argument fully applies.

Optimal alternative robustness in Bayesian Decision Theory.

Fabrizio Ruggeri, Jacinto Martín, David Ríos Insua (2003)

RACSAM

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In Martin et al (2003), we suggested an approach to general robustness studies in Bayesian Decision Theory and Inference, based on ε-contamination neighborhoods. In this note, we generalise the results considering neighborhoods based on norms, specifically, the supremum norm for utilities and the total variation norm for probability distributions. We provide tools to detect changes in preferences between alternatives under perturbations of the prior and/or the utility and the most sensitive...

Overcoming priors anxiety.

G. D'AGOSTINI (1999)

Revista de la Real Academia de Ciencias Exactas Físicas y Naturales

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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...

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).

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.

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? ...

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).