High-dimensional correlation matrix estimation for general continuous data with Bagging technique

• DOI: 10.1007/s10994-022-06138-3
• Publication Date: 2022-03-18T21:02:52Z
• Authors: Chaojie Wang; Jin Du; Xiaodan Fan
• Keywords: Scatter matrix; Positive definiteness

Abstract High-dimensional covariance matrix estimation plays a central role in multivariate statistical analysis. It is well-known that the sample singular when size smaller than dimension of variable, but estimate must be positive-definite. This motivates some modifications to preserve its efficient pairwise covariance. In this paper, we modify correlation using Bagging technique. The proposed estimator flexible for general continuous data. Under mild conditions, show theoretically can ensure positive-definiteness with probability one finite samples. We also prove consistency bootstrap Pearson and our p fixed. Simulation results real application are provided demonstrate method strikes better balance between RMSE likelihood, more robust, other existing estimators.