# An Overview on the Estimation of Large Covariance and Precision Matrices

arXiv: https://arxiv.org/abs/1504.02995 · HTML: https://mlsanity.com/paper/1504.02995/

## Key facts

- Cited by 21 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Apr 2015.

## Built on by (most cited first, 21 of 21)

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- [Block Toeplitz Sparse Precision Matrix Estimation for Large-Scale Interval-Valued Time Series Forecasting](https://mlsanity.com/paper/2504.03322/) (2025)
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## Abstract (arXiv)

Estimating large covariance and precision matrices are fundamental in modern multivariate analysis. The problems arise from statistical analysis of large panel economics and finance data. The covariance matrix reveals marginal correlations between variables, while the precision matrix encodes conditional correlations between pairs of variables given the remaining variables. In this paper, we provide a selective review of several recent developments on estimating large covariance and precision matrices. We focus on two general approaches: rank based method and factor model based method. Theories and applications of both approaches are presented. These methods are expected to be widely applicable to analysis of economic and financial data.