Speaker: Sumanta Basu (Cornell University)
Title: Graphical Models for Stationary Time Series
Abstract: Graphical models offer a powerful framework to capture intertemporal and contemporaneous relationships among the components of a multivariate time series. These relationships are encoded in the multivariate spectral density matrix and its inverse. We will present adaptive thresholding and penalization methods for estimation of these objects under suitable sparsity assumptions. We will discuss new optimization algorithms and investigate consistency of estimation under a double-asymptotic regime where the dimension of the time series increases with sample size.