*Show that the equation-by-equation least-squares estimator Bb X0 X (1 X0 Y is the maximum-likelihood estimator...

*Show that the equation-by-equation least-squares estimator Bb ¼ ðX0 XÞ

(1 X0 Y

is the maximum-likelihood estimator of the regression coefficients B in the multivariate general linear model Y ¼ XB þ E, where the model matrix X is fixed, and the distribution of the errors is "i ; Nmð0; SÞ, with ei and ei 0 independent for i 6¼ i 0

. Show that the MLE of the error-covariance matrix is 1 n Eb0 Eb, where Eb ¼ Y ( XBb.