A latent process model for time series of attributed random graphs
A latent process model for time series of attributed random graphs
复制标题
属性随机图时间序列的潜在过程模型
DOI：
10.1007/s11203-011-9058-y
复制
发表时间：
2011
影响因子：
0.8
通讯作者：
C. Priebe
中科院分区：
文献类型：
--
作者：
N. H. Lee;C. Priebe
我们引入了属性随机图时间序列的潜在过程模型，用于表征一组参与者随着时间的推移而产生的多种关联模式。两个数学上易于处理的近似推导，我们研究了一类测试统计量的说明性的变点检测问题的性能，并证明通过近似分析可以提供有价值的信息推理性能。
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.