votes up 2

r_matrix performs f_test for using dimensions that are asymptotically non-normal

Exception Class:

Raise code

_matrix.shape[0] != J:
                raise ValueError("r_matrix and q_matrix must have the same "
                                 "number of rows")
        Rbq = cparams - q_matrix
        if invcov is None:
            cov_p = self.cov_params(r_matrix=r_matrix, cov_p=cov_p)
            if np.isnan(cov_p).max():
                raise ValueError("r_matrix performs f_test for using "
                                 "dimensions that are asymptotically "
            invcov = np.linalg.pinv(cov_p)
            J_ = np.linalg.matrix_rank(cov_p)
            if J_ < J:
                warnings.warn('covariance of constraints does not have full '
                              'rank. The number of constraints is %d, but '
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