Sensitivity analysis in Gaussian Bayesian networks using a divergence measure

被引：16

作者：

Gomez-Villegas, Miguel A. ^{[1
]}

Main, Paloma

Susi, Rosario

机构：

[1] Univ Complutense Madrid, Dept Stat & Operat Res, Madrid, Spain

[2] Univ Complutense Madrid, Dept Stat & Operat Res 3, Madrid, Spain

来源：

COMMUNICATIONS IN STATISTICS-THEORY AND METHODS | 2007年 / 36卷 / 1-4期

关键词：

Gaussian Bayesian network; Kullback-Leibler divergence; sensitivity analysis;

D O I：

10.1080/03610920600853282

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

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.

引用

页码：523 / 539

页数：17

共 50 条

[21] Sensitivity analysis for Bayesian networks with interval probabilities
Tolo, S.
Patelli, E.
Beer, M.
RISK, RELIABILITY AND SAFETY: INNOVATING THEORY AND PRACTICE, 2017, : 306 - 312
[22] Component Importance and Sensitivity Analysis in Bayesian Networks
Zhong, Xiaopin
Li, Qiu
PROCEEDINGS OF 2013 INTERNATIONAL CONFERENCE ON QUALITY, RELIABILITY, RISK, MAINTENANCE, AND SAFETY ENGINEERING (QR2MSE), VOLS I-IV, 2013, : 320 - 325
[23] SENSITIVITY ANALYSIS FOR PROBABILITY ASSESSMENTS IN BAYESIAN NETWORKS
BLACKMOND, K
IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1995, 25 (06): : 901 - 909
[24] Efficient global sensitivity analysis of biochemical networks using Gaussian process regression
Kurdyaeva, Tamara
Milias-Argeitis, Andreas
2018 IEEE CONFERENCE ON DECISION AND CONTROL (CDC), 2018, : 2673 - 2678
[25] Using Bayesian Networks to Measure Web Service QoS
Chang Guofeng
PROCEEDINGS OF THE 2012 INTERNATIONAL CONFERENCE ON COMMUNICATION, ELECTRONICS AND AUTOMATION ENGINEERING, 2013, 181 : 1233 - 1238
[26] Sensitivity Analysis of Stroke Predictors Using Structural Equation Modeling and Bayesian Networks
Oliveira, Helder C. R.
Yanushkevich, Svetlana
Almekhlafi, Mohammed
2022 IEEE CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY (IEEE CIBCB 2022), 2022, : 187 - 194
[27] On the zero-modified poisson model: Bayesian analysis and posterior divergence measure
Katiane S. Conceição
Marinho G. Andrade
Francisco Louzada
Computational Statistics, 2014, 29 : 959 - 980
[28] On the zero-modified poisson model: Bayesian analysis and posterior divergence measure
Conceicao, Katiane S.
Andrade, Marinho G.
Louzada, Francisco
COMPUTATIONAL STATISTICS, 2014, 29 (05) : 959 - 980
[29] ROBUST BAYESIAN-ANALYSIS USING DIVERGENCE MEASURES
DEY, DK
BIRMIWAL, LR
STATISTICS & PROBABILITY LETTERS, 1994, 20 (04) : 287 - 294
[30] Gaussian Mixture Models for Affordance Learning using Bayesian Networks
Osorio, Pedro
Bernardino, Alexandre
Martinez-Cantin, Ruben
Santos-Victor, Jose
IEEE/RSJ 2010 INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS 2010), 2010,

← 1 2 3 4 5 →