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Posterior regret Γ-minimax estimation in a normal model with asymmetric loss function
The problem of posterior regret Γ-minimax estimation under LINEX loss function is considered. A general form of posterior regret Γ-minimax estimators is presented and it is applied to a normal model with two classes of priors. A situation when the posterior regret Γ-minimax estimator, the most stable estimator and the conditional Γ-minimax estimator coincide is presented.
Predictive sample reuse techniques for censored data.
Predictive sample reuse methods usually applied in low structure aparametric paradigms are shown to be useful in certain high structure situations when conjoined with a Bayesian approach. Particular attention is focused on the incomplete data situation for which two alternative sample reuse approaches are devised. The first involves differential weighting and the second a recursive sample reuse algorithm. These are applied to censored exponential survival data. The exponential approach appears to...
Problemas de decisión en ambiente difuso.
Bajo un planteamiento difuso del Problema General de Decisión Unipersonal, se propone un método que permite definir una función de utilidad para este problema. Dicha función se muestra como una familia de funciones de utilidad, la cual se considera como la "utilidad difusa" que sirve para resolver el problema que se plantea en los distintos contextos.
Problemas de decisión en incertidumbre parcial bajo hipótesis de monotonías.
Se estudia el problema de decisión (Θ,Δ,ρ) cuando Θ es un intervalo finito de R y el decisor posee información acerca de las probabilidades de una partición de Θ en subintervalos, de la monotonía de las f.d.d. en dichos intervalos y de algunas restricciones sobre los momentos de la distribución y ciertos generalizadores de éstas dentro de este contexto.
Problemas finitos de decisión con conocimiento cualitativo de la distribución a priori.
En lo que sigue, abordaremos problemas de decisión en ambiente de riesgo y con experimentación, en donde la distribución de probabilidad a priori sobre los estados de la Naturaleza no es perfectamente conocida, sino que solamente se posee una información cualitativa de la misma. Más concretamente, dados dos estados de la Naturaleza cualesquiera, se conoce a lo más, cuál de ellos es más probable que el otro, si bien no se tiene una idea cuantitativa de esta diferencia de probabilidades.
Problemas tipo en teoría de la decisión.
El objetivo de este artículo es ilustrar las técnicas y los conceptos básicos de la Teoría de la Decisión. Para lograr este objetivo se ha adoptado el problema tipo quizá más sencillo: el problema de la inversión. Este queda caracterizado por dos decisiones alternativas (invertir o no invertir) y dos estados de la naturaleza (apreciación y depreciación). La información adicional adopta la forma de opinión de un experto. El problema se ha resuelto en forma extensa y normal. Las consecuencias se suponen...
Procedures to Determine Optimum Two-Stage Sampling Plans by Attributes .
Proceso de decisión basado en la función de esparcimiento.
Procesos de decisión Bayesiana no paramétricos.
Quasi-Bayesian behaviour: a more realistic approach to decision making?
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 information...
Randomized distributed access to mutually exclusive resources.
Randomized minimax estimators under simple random sampling from a finite population.
Reducibility of statistical structures and decision problems
Rejoinder on: Natural Induction: An objective Bayesian approach.
Relative Measurement and Its Generalization in Decision Making. Why Pairwise Comparisons are Central in Mathematics for the Measurement of Intangible Factors. The Analytic Hierarchy/Network Process.
According to the great mathematician Henri Lebesgue, making direct comparisons of objects with regard to a property is a fundamental mathematical process for deriving measurements. Measuring objects by using a known scale first then comparing the measurements works well for properties for which scales of measurement exist. The theme of this paper is that direct comparisons are necessary to establish measurements for intangible properties that have no scales of measurement. In that case the value...
Robust Bayesian estimation in a normal model with asymmetric loss function
The problem of robust Bayesian estimation in a normal model with asymmetric loss function (LINEX) is considered. Some uncertainty about the prior is assumed by introducing two classes of priors. The most robust and conditional Γ-minimax estimators are constructed. The situations when those estimators coincide are presented.
Robust Bayesian estimation with asymmetric loss function
The problem of robust Bayesian estimation in some models with an asymmetric loss function (LINEX) is considered. Some uncertainty about the prior is assumed by introducing two classes of priors. The most robust and conditional Γ-minimax estimators are constructed. The situations when those estimators coincide are presented.
Secretary Problems with Inspection Costs as a Game.
Semiparametric deconvolution with unknown noise variance
This paper deals with semiparametric convolution models, where the noise sequence has a gaussian centered distribution, with unknown variance. Non-parametric convolution models are concerned with the case of an entirely known distribution for the noise sequence, and they have been widely studied in the past decade. The main property of those models is the following one: the more regular the distribution of the noise is, the worst the rate of convergence for the estimation of the signal’s density...