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Weighted directed networks with a differentially private bi-degree sequence

Authors :
Wang, Qiuping
Zhang, Xiao
Luo, Jing
Ouyang, Yang
Wang, Qian
Publication Year :
2020

Abstract

The $p_0$ model is an exponential random graph model for directed networks with the bi-degree sequence as the exclusively sufficient statistic. It captures the network feature of degree heterogeneity. The consistency and asymptotic normality of a differentially private estimator of the parameter in the private $p_0$ model has been established. However, the $p_0$ model only focuses on binary edges. In many realistic networks, edges could be weighted, taking a set of finite discrete values. In this paper, we further show that the moment estimators of the parameters based on the differentially private bi-degree sequence in the weighted $p_0$ model are consistent and asymptotically normal. Numerical studies demonstrate our theoretical findings.<br />Comment: 19 pages. arXiv admin note: text overlap with arXiv:1705.01715 and arXiv:1408.1156 by other authors

Subjects

Subjects :
Mathematics - Statistics Theory

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2003.11373
Document Type :
Working Paper