Statistics Seminar Series
Thursday, October 2, 4:10pm, MSB 1147 (Colloquium Room)
Refreshments at 3:30pm in MSB 4110 (Statistics Lounge)
Speaker: Xiaotong Shen (Univ. Minnesota, Twin Cities)
Title: “Estimation of a directed acyclic Gaussian graph”
Abstract: Directed acyclic graphs are widely used to describe, among interacting units, causal relations. Causal relations are estimated by reconstructing a directed acyclic graph's structure, presenting a great challenge when the unknown total ordering of a DAG needs to be estimated. In such a situation, it remains unclear if a graph's structure is reconstructable in the absence of an identifiable likelihood with regard to graphs, and in facing super-exponentially many candidate graphs in the number of nodes. In this talk, I will introduce a global approach for observational data and interventional data, to identify all estimable causal directions and estimate model parameters. This approach uses constrained maximum likelihood with nonconvex constraints reinforcing the non-loop requirement to yield an estimated directed acyclic graph, where super-exponentially many constraints characterize the major challenge. Computational issues will be discussed in addition to some theoretical aspects.
This work is joint with Y. Yuan, W. Pan and Z. Wang.