# 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}
}```
• Published 15 August 2021
• Computer Science, Mathematics
• 2021 Winter Simulation Conference (WSC)
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…
1 Citations

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