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Autor Gómez Villegas, Miguel A. |
Documentos disponibles escritos por este autor (42)
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This article develops a method for computing the sensitivity analysis in a Gaussian Bayesian network. The measure presented is based on the Kullback–Leibler divergence and is useful to evaluate the impact of prior changes over the posterior marg[...]![]()
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We introduce a methodology for sensitivity analysis of evidence variables in Gaussian Bayesian networks. Knowledge of the posterior probability distribution of the target variable in a Bayesian network, given a set of evidence, is desirable. How[...]![]()
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Gómez Villegas, Miguel A. ; Main Yaque, Paloma ; Navarro, H. ; Susi García, Rosario | 2010-06-01Our focus is on learning Gaussian Bayesian networks (GBNs) from data. In GBNs the multivariate normal joint distribution can be alternatively specified by the normal regression models of each variable given its parents in the DAG (directed acycl[...]![]()
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Bayesian networks (BNs) have become an essential tool for reasoning under uncertainty in complex models. In particular, the subclass of Gaussian Bayesian networks (GBNs) can be used to model continuous variables with Gaussian distributions. Here[...]![]()
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Gómez Villegas, Miguel A. ; Gómez Sánchez-Manzano, Eusebio ; Marín Diazaraque, Juan Miguel | Academic Press | 2006-02Two conditions are shown under which elliptical distributions are scale mixtures of normal distributions with respect to probability distributions. The issue of finding the mixing distribution function is also considered. As a unified theoretica[...]![]()
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In the problem of testing the point null hypothesis H-0: theta = theta(0) versus H-1: theta not equal theta(0), with a previously given prior density for the parameter theta, we propose the following methodology: to fix an interval of radius eps[...]![]()
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Gómez Sánchez-Manzano, Eusebio ; Gómez Villegas, Miguel A. ; Marín Diazaraque, Juan Miguel | Universidad Complutense de Madrid | 2003In this paper it is taken up a revision and characterization of the class of absolutely continuous elliptical distributions upon a parameterization based on the density function. Their properties (probabilistic characteristics, a±ne transformati[...]![]()
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Sánchez-Manzano, E.G. ; Gómez Villegas, Miguel A. ; Tejada Cazorla, Juan Antonio | Real Academia de Ciencias Exactas, Físicas y Naturales | 1999This paper introduces the Bayesian Dynamic Linear Model to predict the flows (mainly in flood conditions) at a point of a river in successive instants of time, knowing the previous flows at several stations located up the river. The model is fit[...]![]()
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Gómez Villegas, Miguel A. ; Main Yaque, Paloma ; Susi García, Rosario | Elsevier Science INC | 2013-02n this work we study the effects of model inaccuracies on the description of a Gaussian Bayesian network with a set of variables of interest and a set of evidential variables. Using the Kullback-Leibler divergence measure, we compare the output [...]![]()
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In this paper the problem of testing a multivariate point hypothesis is considered. Of interest is the relationship between the p-value and the posterior probability. A Bayesian test for simple H0 V ? D ?0 versus bilateral H0 V 6D 0, with a mixe[...]![]()
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Semblanza biográfica de Thomas Bayes![]()
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Gómez Villegas, Miguel A. ; Sanz San Miguel, Luis | Real Academia Ciencias Exactas Físicas Y Naturales | 2003The problem of testing a point null hypothesis from the Bayesian perspective is considered. The uncertainties are modelled through use of "{contamination class with the class of contaminations including: i) All unimodal distributions and ii). Al[...]