Algebraic Statistics for Network Models
Abstract
This project focused on the family of exponential random graph models (ERGMs) for networks, characterized by global network summary statistics. These models are especially attractive because they are built precisely around the kinds of network characteristics that analysts are concerned with in most practical applications. The team has proposed a systematic program of mathematical research into the algebraic geometric structure of parameter estimation and assessing model fit for these and related statistical models. The team has reached all three of the proposed Phase I measurable milestones and made significant progress toward future proposed work, reaching an additional milestone originally proposed for later phases. In particular, the team has: (1) created new tools for assessing the goodness of fit of models and comparison of models within the ERGM class; and (2) characterized the statistical properties of ERGMs using geometric tools and, specifically, identified when ERGMs are "nice," i.e., not exhibiting near-degeneracies of the sort described in the statistical literature.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 19, 2014
- Accession Number
- ADA601381
Entities
People
- Alessandro Rinaldo
- Sonja Petrović
- Stephen E. Fienberg
Organizations
- Pennsylvania State University