2020
A shrinkage approach to joint estimation of multiple covariance matrices
Hu Z, Hu Z, Dong K, Tong T, Wang Y. A shrinkage approach to joint estimation of multiple covariance matrices. Metrika 2020, 84: 339-374. DOI: 10.1007/s00184-020-00781-3.Peer-Reviewed Original ResearchSample covariance matrixCovariance matrixMultiple covariance matricesPooled sample covariance matrixOptimal shrinkage parameterQuadratic loss functionShrinkage parameterJoint estimationNumber of groupsShrinkage approachShrinkage methodSimulation studyLoss functionMatrixInfinityEstimatorSample sizeEstimationFramework
2017
A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix
Hu Z, Dong K, Dai W, Tong T. A Comparison of Methods for Estimating the Determinant of High-Dimensional Covariance Matrix. The International Journal Of Biostatistics 2017, 13: 20170013. PMID: 28953454, DOI: 10.1515/ijb-2017-0013.Peer-Reviewed Original ResearchConceptsHigh-dimensional covariance matricesCovariance matrixCovariance matrix estimationMatrix estimation methodExtensive simulation studyHigh-dimensional dataStatistical inferenceCovariance matrix estimation methodMatrix estimationComputational challengesInformation theoryEstimation methodSimulation studyHigh dimensionalityLoss functionStatistical testsComparison resultsReal applicationsInteresting comparison resultsComparison of methodsMatrixRecent proposalSample sizeDimensionalityTheory