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Approximate Variational Estimation for a Model of Network Formation

时间:2017-06-08

Statistics Seminar2017-13

Topic:Approximate Variational Estimation for a Model of Network Formation

Speaker:Lingjiong Zhu,Florida State University

Time:Thursday, June 8, 14:00-15:00

Place:Room 217, Guanghua Building 2

Abstract:

We study an equilibrium model of sequential network formation with heterogeneous players. The payoffs depend on the number and composition of direct connections, but also the number of indirect links. We show that the network formation process is a potential game and in the long run the model converges to an exponential random graph (ERGM). Since standard simulation-based inference methods for ERGMs could have exponentially slow convergence, we propose an alternative deterministic method, based on a variational approximation of the likelihood. We compute bounds for the approximation error for a given network size and we prove that our variational method is asymptotically exact, extending results from the large deviations and graph limits literature to allow for covariates in the ERGM. A simple Monte Carlo shows that our deterministic method provides more robust estimates than standard simulation based inference.

Introduction:

Lingjiong Zhu grew up in Shanghai and went to study in England, where he got BA from University of Cambridge in 2008. He then moved to the United States and received PhD from New York University in 2013. After a stint at Morgan Stanley, he went to work at University of Minnesota as Dunham Jackson Assistant Professor, before joining the faculty at Florida State University as an Assistant Professor in 2015.

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