使用uscd_garch工具箱进行对角阵的BEKK-GARCH模型进行估计时，出来的结果如何解释，各个参数对应的系数是哪个？t统计量或者估计标准误差如何看？
具体：
两个序列：2*356
使用模型：[parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores] = diagonal_bekk_T_mvgarch(data,p,q,BEKKoptions);

对应工具箱中的解释：
PURPOSE:
%      To Estimate a diagonal BEKK multivariate GARCH model with T-dist errors.  ****SEE WARNING AT END OF HELP FILE****
%
% USAGE:
%      [parameters, loglikelihood, Ht, likelihoods, stdresid, stderrors, A, B, scores]  = diagonal_bekk_T_mvgarch(data,p,q,options);
%
% INPUTS:
%      data          - A t by k matrix of zero mean residuals
%      p             - The lag length of the innovation process
%      q             - The lag length of the AR process
%      options       - (optional) Options for the optimization(fminunc)
%
% OUTPUTS:
%      parameters    - A (k*(k+1))/2+p*k+q*k+1 vector of estimated parameteters.
%                         For any k set of Innovation or AR parameters X,
%                         diag(X) will give the correct matrix
%                         To recover C, use ivech(parmaeters(1:(k*(k+1))/2), nu is the last parameter
%      loglikelihood - The loglikelihood of the function at the optimum
%      Ht            - A k x k x t 3 dimension matrix of conditional covariances
%      likelihoods   - A t by 1 vector of individual likelihoods
%      stdresid      - A t by k matrix of multivariate standardized residuals
%      stderrors     - A numParams^2 square matrix of robust Standad Errors(A^(-1)*B*A^(-1)*t^(-1))
%      A             - The estimated inverse of the non-robust Standard errors
%      B             - The estimated covariance of the scores
%      scores        - A t by numParams matrix of individual scores
%
%
% COMMENTS:
%      ***************************************************************************************
%      *  THIS FUNCTION INVOLVES ESTIMATING QUITE A FEW PARAMETERS.  THE EXACT NUMBER OF
%      *  PARAMETERS NEEDING TO BE ESTIMATED IS (k*(k+1))/2+pk+qk.  FOR A 5 VARIATE (1,1) MODEL
%      *  THIS INVLOVES 25 PARAMETERS.  IN ADDITION, IT ESTIMATES A SCALAR_BEKK_MVGARCH
%      *  MODEL FOR STARTING VALUES.
%      ***************************************************************************************
%
%
% Author: Kevin Sheppard
% kevin.sheppard@economics.ox.ac.uk
% Revision: 2    Date: 12/31/2001


假设BEKK模型是：

最终估计出来的结果：
parameters：
0.00998706064970756
0.00976385886878744
0.00295361221985619
0.00450853392320618
0.00450826807508813
0.713312528463977
0.713308685586561
11.0999807506309


stderrors
是一个8*8的矩阵


请问各位大侠：模型的系数及其t统计量到底是哪个？