There are no latent variables in the model. Any element below the diagonal of B may be either a fixed zero or a free parameter. The matrix G may contain any number of fixed zeros and any number of free elements. N under the assumption that z is multivariate normal.
Nothing needs to be assumed about the distribution of x .
The conditions for this result can be slightly extended by allowing for some of the error terms to be correlated. This example is based on a fictitious sample covariance matrix assumed to be estimated from 767 cases. 12.128 6.358 19.532 Note that the t-values for the error variances are all equal to 19.532 . This gives the following estimates, standard errors, and t-values for the y ' s . One can alter the data in any way as long as the sample covariance matrix is positive definite.