Methods for estimating sparse and large covariance matrices Covariance and correlation matrices play fundamental roles in every aspect of the analysis of multivariate data collected from a variety of fields including business and economics, health care, engineering, and environmental and physical sciences. High-Dimensional Covariance Estimation provides accessible and comprehensive coverage of the classical and modern approaches for estimating covariance matrices as well as their applications to the rapidly developing areas lying at the intersection of statistics and ma
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
<p>Estimation of high-dimensional covariance matrices is an interesting and important research topic...
Abstract. Estimating covariance matrices is an important part of port-folio selection, risk manageme...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
This thesis considers two problems related to high-dimensional covariance matrices, namely, covarian...
Covariance matrix estimation plays a central role in statistical analyses. In molecular biology, for...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
The thesis concerns estimating large correlation and covariance matrices and their inverses. Two new...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
<p>Estimation of high-dimensional covariance matrices is an interesting and important research topic...
Abstract. Estimating covariance matrices is an important part of port-folio selection, risk manageme...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Covariance matrix estimation plays an important role in statistical analysis in many fields, includi...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
This thesis considers two problems related to high-dimensional covariance matrices, namely, covarian...
Covariance matrix estimation plays a central role in statistical analyses. In molecular biology, for...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
The thesis concerns estimating large correlation and covariance matrices and their inverses. Two new...
Estimating covariance matrices is an important part of portfolio selection, risk management, and ass...
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
Estimating large covariance matrices from small samples is an important problem in many fields. Amon...
<p>Estimation of high-dimensional covariance matrices is an interesting and important research topic...