Not MLE but QMLE

index.html

@@ -27664,7 +27664,7 @@ Y_{t} = \mu + Y_{t-1}  + \varepsilon_t \quad \text{with} \quad \varepsilon_t = \
 <li>We draw <span class="math inline">\(2^{12}= 2048\)</span> trajectories 30 steps ahead</li>
 </ul>
 <h3 id="estimation">Estimation</h3>
-<p>Joint maximum likelihood estimation:</p>
+<p>Joint (quasi) maximum likelihood estimation:</p>
 <p><span class="math display">\[\begin{align*}
     f_{\mathbf{X}_t}(\mathbf{x}_t | \mathcal{F}_{t-1}) = c\left[\mathbf{F}(\mathbf{x}_t;\boldsymbol{\mu}_t, \boldsymbol{\sigma}_{t}^2, \boldsymbol{\nu},
     \boldsymbol{\lambda});\Xi_t, \Theta\right] \cdot \\ \prod_{i=1}^K f_{X_{i,t}}(\mathbf{x}_t;\boldsymbol{\mu}_t, \boldsymbol{\sigma}_{t}^2, \boldsymbol{\nu}, \boldsymbol{\lambda})

index.qmd

@@ -3212,7 +3212,7 @@ $\Lambda(\cdot)$ is a link function:
 
 ### Estimation
 
-Joint maximum likelihood estimation:
+Joint (quasi) maximum likelihood estimation:
 
 \begin{align*}
     f_{\mathbf{X}_t}(\mathbf{x}_t | \mathcal{F}_{t-1}) = c\left[\mathbf{F}(\mathbf{x}_t;\boldsymbol{\mu}_t, \boldsymbol{\sigma}_{t}^2, \boldsymbol{\nu},