A0386
Title: Precision matrix estimation using penalized generalized Sylvester matrix equation
Authors: Vahe Avagyan - Wageningen University and Research (Netherlands) [presenting]
Abstract: Estimating a precision matrix is an important problem in several research fields when dealing with large-scale data. Under high-dimensional settings, one of the most popular approaches is optimizing a Lasso or L1 norm penalized objective loss function. This penalization endorses sparsity in the estimated matrix and improves the accuracy under a proper calibration of the penalty parameter. The problem of minimizing Lasso penalized D-trace loss is demonstrated to be solved by solving a penalized Sylvester matrix equation. Motivated by this method, estimating the precision matrix is proposed using penalized generalized Sylvester matrix equations. A particular estimating equation and a new convex loss function constructed through this equation are developed, which is called the generalized D-trace loss. The performance of the proposed method is assessed using detailed numerical analysis, including simulated and real data. Extensive results show the advantage of the proposed method compared to other estimation approaches in the literature.
