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Statistics Seminar

Identification and Estimation of Graphical Continuous Lyapunov Models Note unusual location

With Mathias Drton (Technical University of Munich)

Identification and Estimation of Graphical Continuous Lyapunov Models

Graphical continuous Lyapunov models offer a new perspective on modeling causally interpretable dependence structure in multivariate data by treating each independent observation as a one-time cross-sectional snapshot of a temporal process. Specifically, the models consider multivariate Ornstein-Uhlenbeck processes in equilibrium. This leads to Gaussian models in which the covariance matrix is determined by the continuous Lyapunov equation. In this setting, each graphical model assumes a sparse drift matrix with support defined by a directed graph. The talk will discuss the identifiability of such sparse drift matrices and their regularized estimation.

Note unusual location

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