Influence measures and stability for graphical models

JOURNAL OF MULTIVARIATE ANALYSIS

卷:147

Article

Bar-Hen, Avner¹  Poggi, Jean-Michel^2,3 

[1] Univ Paris 05, Lab MAP5, Paris, France

[2] Univ Paris Saclay, Univ Paris 11, CNRS, Lab Math Orsay, F-91405 Orsay, France

[3] Univ Paris 05, Paris, France

关键词: Influence measure;    Graphical model;    Robustness;   

DOI  :  10.1016/j.jmva.2016.01.006

来源: Elsevier

【 摘 要 】

Graphical models allow to represent a set of random variables together with their probabilistic conditional dependencies. Various algorithms have been proposed to estimate such models from data. The focus of this paper is on individual observations diagnosis issues. The use of an influence measure is a classical diagnostic method to measure the perturbation induced by a single element, in other terms we consider stability issue through jackknife. For a given graphical model, we provide tools to perform diagnosis on observations. In a second step we propose a filtering of the dataset to obtain a stable network. All along the paper an application to a gene expression dataset illustrates the proposals. (C) 2016 Elsevier Inc. All rights reserved.

【 授权许可】

Free