Penalized Normal Likelihood and Ridge Regularization of Correlation and Covariance Matrices
相关与协方差矩阵的惩罚正态似然和岭正则化
High dimensionality causes problems in various areas of statistics. A particular situation that rarely has been considered is the testing of hypotheses about multivariate regression models in which the dimension of the multivariate response is large. In this article a ridge regularization approach is proposed in which either the covariance or the correlation matrix is regularized to ensure nonsingularity irrespective of the dimensionality of the data. It is shown that the…