A latent process model for time series of attributed random graphs

被引：0
|
作者：
Lee N.H. [1 ]
Priebe C.E. [1 ]
机构：
[1] Johns Hopkins University, Baltimore, MD
来源：
Statistical Inference for Stochastic Processes | 2011年 / 14卷 / 3期
关键词：
Change point; Inference; Latent position model; Latent process model; Random graph;
D O I：
10.1007/s11203-011-9058-y
中图分类号：
学科分类号：
摘要：
We introduce a latent process model for time series of attributed random graphs for characterizing multiple modes of association among a collection of actors over time. Two mathematically tractable approximations are derived, and we examine the performance of a class of test statistics for an illustrative change-point detection problem and demonstrate that the analysis through approximation can provide valuable information regarding inference properties. © 2011 The Author(s).
引用
收藏
页码：231 / 253
页数：22
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