Biblioteca de la Universidad Complutense de Madrid

Sensitivity Analysis in Gaussian Bayesian Networks Using a Divergence Measure

Impacto



Gómez Villegas, Miguel A. y Main Yaque, Paloma y Susi García, Rosario (2007) Sensitivity Analysis in Gaussian Bayesian Networks Using a Divergence Measure. Communications in statistics. Theory and methods, 36 (1-4). pp. 523-539. ISSN 1532-415X

[img] PDF
138kB

URL Oficial: http://www.tandfonline.com/loi/lsta20



Resumen

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 marginal density of the target variable in the network. We find that some changes do not disturb the posterior marginal density of interest. Finally, we describe a method to compare different sensitivity measures obtained depending on where the inaccuracy was. An example is used to illustrate the concepts and methods presented.


Tipo de documento:Artículo
Palabras clave:Gaussian Bayesian network, Kullback–Leibler divergence, Sensitivity analysis
Materias:Ciencias > Matemáticas > Estadística aplicada
Código ID:14566
Depositado:15 Feb 2012 11:30
Última Modificación:04 Mar 2016 15:30

Sólo personal del repositorio: página de control del artículo