Commit bf484ed4 by Michel Juillard

### internal documentation minor changes

parent f3bc4c25
 ... ... @@ -134,19 +134,27 @@ $\Sigma_y$. The autocovariance matrix of $y_t$ and $y_{t-1}$ is defined as \begin{align*} \mbox{cov}\left(y_t,y_{t-1}\right) &=E\left\{\hat y_t\hat y_{t-1}'\right\}\\ \mbox{cov}\left(y_t,y_{t-1}\right) &=E\left\{y_t y_{t-1}'\right\}\\ &= E\left\{\left(g_y \hat y_{t-1}+g_u u_t\right)\hat y_{t-1}'\right\}\\ &= g_y\Sigma_y \end{align*} by recursion we have that $\mbox{corr}\left(y_t,y_{t-k}\right)=E_\left{y_ty_{t-k}'\right\}=g_y^k\Sigma_y$. by recursion we have \begin{align*} \mbox{cov}\left(y_t,y_{t-k}\right) &=E\left\{y_t y_{t-k}'\right\} \\ &=g_y^k\Sigma_y \end{align*} The autocorrelation matrix is then $\begin{equation*} \mbox{corr}\left(y_t,y_{t-k}\right) = \mbox{diag}(\sigma_y)^{-1}E_\left{y_ty_{t-k}'\right\}\mbox{diag}(\sigma_y)^{-1}$ \mbox{diag}\left(\sigma_y\right)^{-1}E\left\{y_ty_{t-k}'\right\}\mbox{diag}\left(\sigma_y\right)^{-1} \end{equation*} where $\mbox{diag}\left(\sigma_y\right)$ is a diagonal matrix with the standard deviations on the main diagonal. *** Function <> - [[m2html:lyapunov_symm.html>>][M2HTML link]] - TO BE DONE * Estimation ** estimation Dynare command *estimation* calls function [[dynare\_estimation.m]] ... ...
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