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This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors, a linear com-bination of some ...
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
In a high dimensional linear regression model, we propose a new procedure for testing statistical significance of a subset of regression coefficients. Specifically,we employ the partial covariances be...
The na?ve Bayes approach is one of the most popular methods used for classi?cation. Nevertheless, how to test its statistical signi?cance under an ultra-high-dimensional (UHD) setup is not well unders...
Motivated by the latest effort to employ banded matrices to esti-mate a high-dimensional covariance Σ, we propose a test for Σ being banded with possible diverging bandwidth. The test is adaptive to t...
This paper considers the maximum generalized empirical likelihood (GEL) estimation and inference on parameters identified by high dimensional moment restrictions with weakly dependent data when the di...
We consider testing regression coefficients in high dimensional generalized linear mod-els. By modifying a test statistic proposed by Goeman et al. (2011) for large but fixed dimensional settings, we ...
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
We consider two alternative tests to the Higher Criticism test of Donoho and Jin (2004) for high dimensional means under the spar-sity of the non-zero means for sub-Gaussian distributed data with unkn...
We consider a multivariate time series model which represents a high dimensional vector process as a sum of three terms: a linear regression of some observed regressors,a linear combination of some la...
Influence diagnosis is important since presence of influential ob-servations could lead to distorted analysis and misleading interpreta-tions. For high dimensional data, it is particularly so, as the ...

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