# Estimation When Both Covariance and Precision Matrices are Sparse

@article{MacNamara2021EstimationWB, title={Estimation When Both Covariance and Precision Matrices are Sparse}, author={Shev MacNamara and Erik Schl{\"o}gl and Zdravko I. Botev}, journal={2021 Winter Simulation Conference (WSC)}, year={2021}, pages={1-11} }

We offer a method to estimate a covariance matrix in the special case that both the covariance matrix and the precision matrix are sparse - a constraint we call double sparsity. The estimation method is maximum likelihood, subject to the double sparsity constraint. In our method, only a particular class of sparsity pattern is allowed: both the matrix and its inverse must be subordinate to the same chordal graph. Compared to a naive enforcement of double sparsity, our chordal graph approach…

## One Citation

### Robust sparse precision matrix estimation for high-dimensional compositional data

- Computer ScienceStatistics & Probability Letters
- 2022

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