Characterizations of multivariate normality II. Through linear regressions

It is established that a vector (X'1, X'2, ..., X'k) has a multivariate normal distribution if (i) for each Xi the regression on the rest is linear, (ii) the conditional distribution of X1 about the regression does not depend on the rest of the variables, and (iii) the conditional distribution of X2 about the regression does not depend on the rest of the variables, provided that the regression coefficients satisfy some more conditions that those given by [4]J. Multivar. Anal. 6 81-94].