Estimation of Graphical Models using the ℓ₁,₂ Norm

Mon, 01 Oct 2018 00:00:00 +0000

In this article, Chiong and Moon develop estimation techniques for graphical models based on the ℓ₁,₂ norm penalty. The method promotes group sparsity in the inverse covariance matrix, allowing practitioners to uncover network structures in data sets with many variables. The technique has applications in econometrics and machine learning.

High-Dimensional Econometrics |

Estimation of Graphical Models using the ℓ₁,₂ Norm