The distribution of the largest latent root of the covariance matrix calculated from a sample from the normal normalitive multivariate population with population covariance matrix σ2 I are presented ...

Analysis of covariance combines some of the features of both regression and analysis of variance. Typically, a continuous variable (the covariate) is introduced into the model of an ...

We compute the limiting distributions of the largest eigenvalue of a complex Gaussian sample covariance matrix when both the number of samples and the number of variables in each sample become large.

Example 8.3: Regression This example shows a regression module that calculates statistics not calculated by the two previous examples: /* Regression Routine ...