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Computes a multivariate version of the Jarque-Bera test for normality. Note that there are more sophisticated versions of this (for instance, Doornik and Hansen, "An Omnibus Test for Univariate and Multivariate Normality"). This just transforms the input residual series to uncorrelated components (using an eigenbased factorization if not provided by the user) and sums up the univariate JB statistics from those.



@MVJB( options) u start end

Parameters

u	VECTOR of SERIES
start end	Range for the calculation [by default, the maximum combined range of the u's]

Options
Note: one of these must be supplied.
SIGMA=SYMMETRIC covariance matrix of u
FACTOR=RECTANGULAR factor of the covariance matrix of u.
HMATRICES=SERIES[SYMM] of time-varying covariance matrices.

When I used this procedure, I got this error message:

@mvjb(hmatrices=hh) u
## OP3. This Instruction Does Not Have An Option HMA
>>>>hmatrices=<<<<

Thanks.

The procedure posted here has it, and the 8.2 distribution has it. So you must be using an older version of the procedure.