174 citations · 415 across the 18 of their papers we have counts for
4 papers · 1 filter
Pseudo-likelihood-based -estimation of random graphs with dependent edges and parameter vectors of increasing dimension
Jonathan R. Stewart, Michael Schweinberger
An important question in statistical network analysis is how to estimate models of discrete and dependent network data with intractable likelihood functions, without sacrificing co…
A note on the role of projectivity in likelihood-based inference for random graph models
Michael Schweinberger, Pavel N. Krivitsky, Carter T. Butts
There is widespread confusion about the role of projectivity in likelihood-based inference for random graph models. The confusion is rooted in claims that projectivity, a form of m…
Consistent structure estimation of exponential-family random graph models with block structure
Michael Schweinberger
We consider the challenging problem of statistical inference for exponential-family random graph models based on a single observation of a random graph with complex dependence. To…
Concentration and consistency results for canonical and curved exponential-family models of random graphs
Michael Schweinberger, Jonathan Stewart
Statistical inference for exponential-family models of random graphs with dependent edges is challenging. We stress the importance of additional structure and show that additional…