publication . Doctoral thesis . 2016

Contributions to Large Covariance and Inverse Covariance Matrices Estimation

Kang, Xiaoning;
Open Access
  • Published: 25 Aug 2016
  • Publisher: Virginia Tech
  • Country: United States
Estimation of covariance matrix and its inverse is of great importance in multivariate statistics with broad applications such as dimension reduction, portfolio optimization, linear discriminant analysis and gene expression analysis. However, accurate estimation of covariance or inverse covariance matrices is challenging due to the positive definiteness constraint and large number of parameters, especially in the high-dimensional cases. In this thesis, I develop several approaches for estimating large covariance and inverse covariance matrices with different applications. In Chapter 2, I consider an estimation of time-varying covariance matrices in the analysis ...
free text keywords: Covariance matrix; modified Cholesky decomposition; sparse estimation
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