ALAAMEE: Open-source software for fitting autologistic actor attribute models

Abstract

The autologistic actor attribute model (ALAAM) is a model for social influence, derived from the more widely known exponential-family random graph model (ERGM). ALAAMs can be used to estimate parameters corresponding to multiple forms of social contagion associated with network structure and actor covariates. This work introduces ALAAMEE, open-source Python software for estimation, simulation, and goodness-of-fit testing for ALAAM models. ALAAMEE implements both the stochastic approximation and equilibrium expectation (EE) algorithms for ALAAM parameter estimation, including estimation from snowball sampled network data. It implements data structures and statistics for undirected, directed, and bipartite networks. We use a simulation study to assess the accuracy of the EE algorithm for ALAAM parameter estimation and statistical inference, and demonstrate the use of ALAAMEE with empirical examples using both small (fewer than 100 nodes) and large (more than 10 000 nodes) networks.

Provisionally accepted for publication

References in corpus (7)

• Array Programming with NumPy
• Homophily and Contagion Are Generically Confounded in Observational Social Network Studies
• Batch means and spectral variance estimators in Markov chain Monte Carlo
• The Penalty Method for Random Walks with Uncertain Energies
• ergm 4: New features
• Exponential random graph model parameter estimation for very large directed networks
• Fast Maximum Likelihood estimation via Equilibrium Expectation for Large Network Data