What are good tests to check if the data is generated by multivariate jointly gaussian distribution.
I know $\chi^2$ test is commonly used as a goodness of fit metric but I did not understand how to use it for multidimensional random vector case. Most of the examples I saw were for univariate cases.
An example would help a lot.
Note: the covariance matrix isn't diagonal. No assumption of independent variables.
