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Gaussian Bayesian networks are graphical models that represent the dependence structure of a multivariate normal random variable with a directed acyclic graph (DAG). In Gaussian Bayesian networks the output is usually the conditional distributio[...]texto impreso
The multivariate exponential power family is considered for n-dimensional random variables, Z, with a known partition Z equivalent to (Y, X) of dimensions p and n - p, respectively, with interest focusing on the conditional distribution Y vertic[...]texto impreso
We relate the classes of life distributions based on notions of aging with those that depend on the tail behaviour. This last classification introduces the concepts of outlier-neutral, outlier-prone and outlier- resistant distributions. We prove[...]texto impreso
Gómez Villegas, Miguel A. ; Main Yaque, Paloma ; Sanz San Miguel, Luis ; Navarro Veguillas, Hilario | North Holland | 2004-01In this paper the asymptotic relationship between the classical p-value and the infimum (over all unimodal and symmetric distributions) of the posterior probability in the point null hypothesis testing problem is analyzed. It is shown that the r[...]texto impreso
A Bayesian test for the point null testing problem in the multivariate case is developed. A procedure to get the mixed distribution using the prior density is suggested. For comparisons between the Bayesian and classical approaches, lower bounds[...]texto impreso
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Fresno Vara, Juan Angel ; Main Yaque, Paloma ; y, otros | American Association of Cancer Research | 2015-06-01Better knowledge of the biology of breast cancer has allowed the use of new targeted therapies, leading to improved outcome. High-throughput technologies allow deepening into the molecular architecture of breast cancer, integrating different lev[...]texto impreso
The problem of modeling Bayesian networks with continuous nodes deals with discrete approximations and conditional linear Gaussian models. In this article we have considered the possibility of using the exponential power family as conditional pr[...]texto impreso
Gómez Villegas, Miguel A. ; Main Yaque, Paloma ; Navarro Veguillas, Hilario ; Susi, Rosario | Pergamon-Elsevier | 2011In this work, we evaluate the sensitivity of Gaussian Bayesian networks to perturbations or uncertainties in the regression coefficients of the network arcs and the conditional distributions of the variables. The Kullback–Leibler divergence mea[...]texto impreso
To evaluate the impact of model inaccuracies over the network’s output, after the evidence propagation, in a Gaussian Bayesian network, a sensitivity measure is introduced. This sensitivity measure is the Kullback–Leibler divergence and yields d[...]texto impreso
Gamez-Pozo, A. ; Trilla-Fuentes, L. ; Berges-Soria, J. ; Selevsek, N. ; López-Vacas, R. ; Díaz-Almiron, M. ; Nanni,, P. ; Arevalillo, J. M. ; Navarro, H. ; Grossmann, J. ; Moreno, F. G. ; Rioja, R. G. ; Prado-Vazquez, G. ; Zapater-Moros, A. ; Main Yaque, Paloma ; Feliu, J. ; del Prado, P. ; Zamora, P. ; Ciruelos, E. ; Espinosa, E. ; Vara, J. A.F. | Nature Publishing Group | 2017Breast cancer is a heterogeneous disease comprising a variety of entities with various genetic backgrounds. Estrogen receptor-positive, human epidermal growth factor receptor 2-negative tumors typically have a favorable outcome; however, some pa[...]texto impreso
To determine the effect of a set of inaccurate parameters in Gaussian Bayesian networks, it is necessary to study the sensitive of the model. With this aim we propose a sensitivity analysis based on comparing two differents models: the original [...]texto impreso
The asymptotic behavior in the right tail of the hazard rate function is considered to compare probability distributions. Using this tail ordering, the position of the posterior distribution with respect to the prior and the likelihood distribut[...]texto impreso
This paper introduces a n-way sensitivity analysis for Gaussian Bayesian networks where it studies the joint effect of variations in a set of similar parameters. The aim is to determine the sensitivity of the model when the parameters that desc[...]texto impreso
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[...]
