4 papers
Uniform Central Limit Theorems for Degree Distributions of Sparse Graphon Models
Robert Lunde, Soumendra Lahiri
The degree distribution is among the most basic summaries of a network, yet no functional limit theorem for the empirical degree distribution of graphon models has been available,…
Central Limit Theorems and Network-Free Inference for Heterogeneous Spatial Autoregressions on Sparse Graphons
Wei Li, Robert Lunde
Network dependence is widely regarded as a fundamental obstacle to inference: outcomes linked through a graph are not independent, the graph is rarely observed in full, and models…
Assumption-lean Inference for Network-linked Data
Wei Li, Nilanjan Chakraborty, Robert Lunde
We consider statistical inference for network-linked regression problems, where covariates may include network summary statistics computed for each node. In settings involving netw…
Statistical Inference for Subgraph Frequencies of Exchangeable Hyperedge Models
Ayoushman Bhattacharya, Nilanjan Chakraborty, Robert Lunde
In statistical network analysis, models for binary adjacency matrices satisfying vertex exchangeability are commonly used. However, such models may fail to capture key features of…