Motivated by the latest effort to employ banded matrices to estimate a high-dimensional covariance Σ , we propose a test for Σ being banded with possible diverging bandwidth. The test is adaptive to the “large p , small n ” situations without assuming a specific parametric distribution for the data. We also formulate a consistent estimator for the bandwidth of a banded high-dimensional covariance matrix. The properties of the test and the bandwidth estimator are investigated by theoretical evaluations and simulation studies, as well as an empirical analysis on a protein mass spectroscopy data
This is an expository paper that reviews recent developments on optimal estimation of structured hig...
This paper proposes a new test for testing the equality of two covariance matrices Σ1 and Σ2 in the ...
This thesis is concerned about statistical inference for the population covariance matrix in the hig...
Motivated by the latest effort to employ banded matrices to estimate a high-dimensional covariance S...
Many statistical analysis procedures require a good estimator for a high-dimensional covariance matr...
The banding estimator of Bickel and Levina and its tapering version of Cai, Zhang, and Zhou are impo...
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (...
We propose a test for a high-dimensional covariance being banded with possible diverging bandwidth. ...
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which th...
The covariance matrices are essential quantities in econometric and statistical applications includi...
Test statistics for sphericity and identity of the covariance matrix are presented, when the data ar...
We consider a class of vector autoregressive models with banded coefficient matrices. The setting re...
Banding the inverse of covariance matrix has become a popular technique to estimate a high dimension...
Testing covariance structure is of significant interest in many areas of statistical analysis and co...
Many applications of modern science involve a large number of parameters. In many cases, the ...
This is an expository paper that reviews recent developments on optimal estimation of structured hig...
This paper proposes a new test for testing the equality of two covariance matrices Σ1 and Σ2 in the ...
This thesis is concerned about statistical inference for the population covariance matrix in the hig...
Motivated by the latest effort to employ banded matrices to estimate a high-dimensional covariance S...
Many statistical analysis procedures require a good estimator for a high-dimensional covariance matr...
The banding estimator of Bickel and Levina and its tapering version of Cai, Zhang, and Zhou are impo...
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (...
We propose a test for a high-dimensional covariance being banded with possible diverging bandwidth. ...
We introduce a new sparse estimator of the covariance matrix for high-dimensional models in which th...
The covariance matrices are essential quantities in econometric and statistical applications includi...
Test statistics for sphericity and identity of the covariance matrix are presented, when the data ar...
We consider a class of vector autoregressive models with banded coefficient matrices. The setting re...
Banding the inverse of covariance matrix has become a popular technique to estimate a high dimension...
Testing covariance structure is of significant interest in many areas of statistical analysis and co...
Many applications of modern science involve a large number of parameters. In many cases, the ...
This is an expository paper that reviews recent developments on optimal estimation of structured hig...
This paper proposes a new test for testing the equality of two covariance matrices Σ1 and Σ2 in the ...
This thesis is concerned about statistical inference for the population covariance matrix in the hig...