Sample Covariance Matrices and the Marčenko-Pastur Law
The sample covariance matrix is a most important random matrix in multivariate statistical inference. It is fundamental in hypothesis testing, principal component analysis, factor analysis, and discrimination analysis. Many test statistics are defined by its eigenvalues.
KeywordsCharacteristic Sequence Sample Covariance Single Edge Sample Covariance Matrix Sample Covariance Matrice
Unable to display preview. Download preview PDF.