Tests for differential Gaussian Bayesian networks based on quadratic inference functions

Xianzheng Huang and Hongmei Zhang

Computational Statistics & Data Analysis, 2021, vol. 159, issue C

Abstract: Hypotheses testing procedures based on quadratic inference functions are proposed to test whether two Gaussian Bayesian networks are differential in structure, strength of associations between nodes, or both. Bootstrap procedures are developed to estimate p-values to quantify the statistical significance of the tests. Operating characteristics of these testing procedures are investigated using synthetic data in simulation experiments. Additionally, the proposed methods are applied to flow cytometry data from a designed experiment, and data of bile acids from an observational study in the Alzheimer’s Disease Neuroimaging Initiative.

Keywords: Directed acyclic graph; Information criterion; Pair bootstrap; Topological ordering; Wild bootstrap (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:eee:csdana:v:159:y:2021:i:c:s0167947321000438

DOI: 10.1016/j.csda.2021.107209

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