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Abstract:
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Networks show up in a variety of applications, starting from social networks to brain networks in neuroscience, from recommender systems to the internet, from who-eats-whom networks in ecosystems to protein protein interaction networks. An important question that often arises is centered around estimating the underlying distribution of network statistics, like eigenvalues, subgraph densities, etc. In this talk I will discuss some recent work on subsampling and the jackknife for these inferential tasks. Despite the dependence of network data induced by edges between pairs of nodes, under the graphon model, we show that jackknife and subsampling largely behave similarly to their IID counterparts. This is joint work with Robert Lunde and Qiaohui Lin.
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