@Article{JCM-39-5,
author = {Lv, Didi and Zhang, Xiaoqun},
title = {A Greedy Algorithm for Sparse Precision Matrix Approximation},
journal = {Journal of Computational Mathematics},
year = {2021},
volume = {39},
number = {5},
pages = {693--707},
abstract = {<p style="text-align: justify;">Precision matrix estimation is an important problem in statistical data analysis. This paper proposes a sparse precision matrix estimation approach, based on CLIME estimator and an efficient algorithm GISS$^{{\rho}}$ that was originally proposed for $l_1$ sparse signal recovery in compressed sensing. The asymptotic convergence rate for sparse precision matrix estimation is analyzed with respect to the new stopping criteria of the proposed GISS$^{{\rho}}$ algorithm. Finally, numerical comparison of GISS$^{\rho}$ with other sparse recovery algorithms, such as ADMM and HTP in three settings of precision matrix estimation is provided and the numerical results show the advantages of the proposed algorithm.</p>},
issn = {1991-7139},
doi = {https://doi.org/10.4208/jcm.2005-m2019-0151},
url = {https://global-sci.com/article/84266/a-greedy-algorithm-for-sparse-precision-matrix-approximation}
}