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Regression Models for Networks

Constructing probability models for networks is difficult, and parameters seldom describe natural quantities. This talk will discuss 2 approaches for constructing regression models which directly attempt to estimate reasonably interesting quantities. These approaches are illustrated with (HIV virus) genetic data and social network data. If time permits, methods for visualizing these models and how they fit the data, using Orca, will be discussed.