Joint density of eigenvalues in spiked multivariate models
Joint density of eigenvalues in spiked multivariate models
The classical methods of multivariate analysis are based on the eigenvalues of one or two sample covariance matrices. In many applications of these methods, for example, to high‐dimensional data, it is natural to consider alternative hypotheses that are a low‐rank departure from the null hypothesis. For rank 1 alternatives, this …