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dec vect[series] eps(n)
dec vect fullbeta(2*n+2)
*
* Do univariate GARCH models. Save the standardized residuals
* into eps(i). Copy the coefficients into the proper slots in
* the full beta matrix.
*
do i=1,n
   garch(p=1,q=1,resids=r,hseries=h) / x(i)
   set eps(i) = r/sqrt(h)
   do j=1,2
      compute fullbeta(n*(j-1)+i)=%beta(j)
   end do j
end do i

*
* Compute the covariance matrix of the standardized residuals
*
vcv(matrix=rr)
# eps

*
* Create the series[symm] uu (outer product of residuals). Make
* it the unconditional value prior to the sample.
*
dec series[symm] uu q
gset uu %regstart() %regend() = %outerxx(%xt(eps,t))
gset uu 1 %regstart()-1 = rr
gset q  = rr

*
* Log likelihood for the DCC phase, taking the residuals as given
*
nonlin a b
dec frml[symm] qf
frml qf   = (1-a-b)*rr+a*uu{1}+b*q{1}
frml logl =q=qf, %logdensity(%cvtocorr(q),%xt(eps,t))
compute b=.10,a=.010
maximize logl 1

* Compute the estimates into the final two slots in fullbeta
*
compute fullbeta(2*n+1)=%beta(1),fullbeta(2*n+2)=%beta(2)