Missing values in @LOGL series at current coefficients at observation 1 in "DO_ BVGARCH.ML(SHOWOPTS, M=100, C=1E-5)"
LogL estimates are not valid
LogL estimates are not valid in "SCALAR LR =-2*( EQ1.@LOGL + EQ2.@LOGL - BVGARCH.@LOGL )"
LR is not defined in "SCALAR LR_PVAL =1 - @CCHISQ(LR,1)"
总是出现以上错误提示，求教高手解答，还有两个问题，一、alpha、beta的初值怎么给？二、alpha（1）、alpha（2）、alpha（3）、alpha（4）这几个值对应系数矩阵里的元素是（1,1）、（1,2）、（2,1）、（2,2）还是（1,1）、（2,1）、（1,2）、（2,2）？毕业论文急用，求各位大侠多多帮忙！我的qq号码：908087197，有知道答案的欢迎赐教！
估计模型如下：

smpl @all
series y1=hs_niu
series y2=dax_niu
sample s0 1 280
sample s1 1 279
smpl s0
equation eq1.arch(m=100,c=1e-5) y1 c
equation eq2.arch(m=100,c=1e-5) y2 c
coef(2) mu
    mu(1)=eq1.c(1)
    mu(2)=eq2.c(1)
coef(3) omega
    omega(1)=(eq1.c(2))^.5
    omega(2)=0
    omega(3)=(eq2.c(2))^.5
coef(4) alpha
     alpha(1) = (eq1.c(3))^.5
     alpha(2) = (eq1.c(3))^.5
     alpha(3) = (eq1.c(3))^.5
     alpha(4) = (eq2.c(3))^.5
coef(4) beta
      beta(1)= (eq1.c(4))^.5
      beta(2)= (eq2.c(4))^.5
      beta(3)= (eq1.c(4))^.5
      beta(4)= (eq2.c(4))^.5
!mlog2pi = 2*log(2*@acos(-1))
series cov_y1y2 = @cov(y1-mu(1), y2-mu(2))
series var_y1 = @var(y1)
series var_y2 = @var(y2)
series sqres1 = (y1-mu(1))^2
series sqres2 = (y2-mu(2))^2
series res1res2 = (y1-mu(1))*(y2-mu(2))
logl bvgarch
bvgarch.append @logl logl
bvgarch.append sqres1 = (y1-mu(1))^2
bvgarch.append sqres2 = (y2-mu(2))^2
bvgarch.append res1res2 = (y1-mu(1))*(y2-mu(2))

bvgarch.append var_y1= omega(1)^2 +( beta(1)^2*var_y1(-1)+2*beta(1)*beta(2)*cov_y1y2(-1)+beta(2)^2*var_y2(-1) )+(alpha(1)^2*sqres1(-1)+2*alpha(1)*alpha(2)*res1res2(-1)+alpha(2)^2*sqres2(-1))
bvgarch.append var_y2  = omega(3)^2+omega(2)^2 + (beta(4)^2*var_y2(-1) +2*beta(4)*beta(3)*cov_y1y2(-1)+beta(3)^2*var_y1(-1) )+ (alpha(4)^2*sqres2(-1)+2*alpha(4)*alpha(3)*res1res2(-1)+alpha(3)^2*sqres1(-1))
bvgarch.append cov_y1y2 = omega(1)*omega(2) + (beta(1)*beta(2)*var_y1(-1)+(beta(2)*beta(3)+beta(4)*beta(1))*cov_y1y2(-1)+beta(3)*beta(4)*var_y2(-1)) + (alpha(1)*alpha(2)*sqres1(-1)+(alpha(2)*alpha(3)+alpha(1)*alpha(4))*res1res2(-1)+alpha(3)*alpha(4)*sqres2(-1))

bvgarch.append deth = var_y1*var_y2 - cov_y1y2^2
bvgarch.append invh1 = var_y2/deth
bvgarch.append invh3 = var_y1/deth
bvgarch.append invh2 = -cov_y1y2/deth

bvgarch.append logl =-0.5*(!mlog2pi + (invh1*sqres1+2*invh2*res1res2+invh3*sqres2) + log(deth))
smpl s1
bvgarch.ml(showopts, m=100, c=1e-5)
show bvgarch.output
graph varcov.line var_y1 var_y2 cov_y1y2
show varcov
scalar lr = -2*( eq1.@logl + eq2.@logl - bvgarch.@logl )
scalar lr_pval = 1 - @cchisq(lr,1)