Displaying similar documents to “Topologies associated to some decision statistical functions”

Optimal alternative robustness in Bayesian Decision Theory.

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

RACSAM

Similarity:

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...

Quasi-Bayesian behaviour: a more realistic approach to decision making?

Francisco Javier Girón, Sixto Ríos (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

In this paper the theoretical and practical implications of dropping -from the basic Bayesian coherence principles- the assumption of comparability of every pair of acts is examined. The resulting theory is shown to be still perfectly coherent and has Bayesian theory as a particular case. In particular we question the need of weakening or ruling out some of the axioms that constitute the coherence principles; what are their practical implications; how this drive to the notion of partial...

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

Similarity:

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).

Cross additivity - an application

Sandra Saraiva Ferreira, Dário Ferreira, João Tiago Mexia (2006)

Discussiones Mathematicae Probability and Statistics

Similarity:

We try to show that Discriminant Analysis can be considered as a branch of Statistical Decision Theory when viewed from a Bayesian approach. First we present the necessary measure theory results, next we briefly outline the foundations of Bayesian Inference before developing Discriminant Analysis as an application of Bayesian Estimation. Our approach renders Discriminant Analysis more flexible since it gives the possibility of classing an element as belonging to a group of populations....

The quadratic scoring rule as a basis for experiment comparison.

Pilar García Carrasco (1984)

Qüestiió

Similarity:

In this paper, the role of strictly proper quadratic utility measures in Bayesian inference and experiment comparison is investigated. This utility function, which is not local, provides a good basis for the resolution of many real situations which are not purely inferential. By recognizing the decision problem underlying statistical inference, we obtain the criteria for experiment comparison based on the quadratic scoring rule. Properties and relations with other criteria are studied,...

Overcoming priors anxiety.

G. D'AGOSTINI (1999)

Revista de la Real Academia de Ciencias Exactas Físicas y Naturales

Similarity:

On not being rational.

I. Richard Savage (1980)

Trabajos de Estadística e Investigación Operativa

Similarity:

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? ...