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Meeting # 942 7359 5552

Zoom Meeting # 942 7359 5552

Abstract:

Network data are relational data that measure interactions or relationships between elements of a population of interest. Examples include social networks where individuals might relate to one another or interact with one another, as well as gene regulatory networks where genes can interact with one another. Network data are often represented as a graph with a set of nodes representing the elements of a population of interest and a set of edges which represent the relational data between elements of the population. Often, the complex mechanisms that give rise to the networks of our world induce dependence among edges in the network. A canonical example of this is transitivity in personal sentiment in friendship networks, where two people are more likely to be friends if they have a common friend. Statistical analyses of network data frequently are in the context of a single observation of the network, which in statistical language means we must perform inference based on a single collection of potentially dependent random variables, presenting numerous challenges to be overcome. This talk presents new developments in the statistical analysis of network data with dependent edges. Specific topics will include the estimation of statistical models for networks and the consistency of empirical distributions of sequences of graph statistics in contexts of networks with dependent edges. 

Speaker's Bio

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