Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  considers improving the por of tests for the identity and sphericity hypotheses regarding high dimensional covariance matrices. The por improvement is achieved by employing the banding estimator for the covariance matrices, which leads to significant reduction in the variance of the test statistics in high dimension. Theoretical justification and simulation experiments are provided to ensure the validity of the proposed tests. The tests are used to analyze a dataset from an acute lymphoblastic leukemia gene expression study for an illustration.
['Liuhua Peng', 'Song Xi Chen', 'Wen Zhou']
I am writing a research paper on a idea More powerful tests for sparse high-dimensional covariances matrices
[{"from": "human", "value": "I am writing a research paper on a idea More powerful tests for sparse high-dimensional covariances matrices"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  considers improving the por of tests for the identity and sphericity hypotheses regarding high dimensional covariance matrices. The por improvement is achieved by employing the banding estimator for the covariance matrices, which leads to significant reduction in the variance of the test statistics in high dimension. Theoretical justification and simulation experiments are provided to ensure the validity of the proposed tests. The tests are used to analyze a dataset from an acute lymphoblastic leukemia gene expression study for an illustration."}]