Trying to add boldsymbol as package to mathjax

Author: VisruthSK

inst/pkgdown/templates/head.html

@@ -27,15 +27,18 @@
 
 {{#uses_mathjax}}
 <!-- mathjax math -->
-<script src="https://cdn.jsdelivr.net/npm/mathjax@3.2.2/es5/tex-mml-chtml.js"
-  integrity="sha256-MASABpB4tYktI2Oitl4t+78w/lyA+D7b/s9GEP0JOGI=" crossorigin="anonymous"></script>
 <script>
   window.MathJax = {
+    loader: { load: ['[tex]/boldsymbol'] },
+    tex: { packages: { '[+]': ['boldsymbol'] } },
     chtml: {
       fontURL: "https://cdn.jsdelivr.net/npm/mathjax@3.2.2/es5/output/chtml/fonts/woff-v2"
     }
   };
 </script>
+<script src="https://cdn.jsdelivr.net/npm/mathjax@3.2.2/es5/tex-mml-chtml.js"
+  integrity="sha256-MASABpB4tYktI2Oitl4t+78w/lyA+D7b/s9GEP0JOGI=" crossorigin="anonymous">
+  </script>
 {{/uses_mathjax}}
 
 {{#lightswitch}}

vignettes/Example.rmd

@@ -25,3 +25,32 @@ print("Done!")
 ```
 
 Above should print two lines.
+
+## "Likelihood" from [`rstanarm`](https://mc-stan.org/rstanarm/articles/lm#likelihood)
+
+The likelihood for one observation under a linear model can be written as a
+conditionally normal PDF
+$$\frac{1}{\sigma_{\epsilon} \sqrt{2 \pi}} 
+  e^{-\frac{1}{2} \left(\frac{y - \mu}{\sigma_{\epsilon}}\right)^2},$$
+where $\mu = \alpha + \mathbf{x}^\top \boldsymbol{\beta}$ is a linear predictor
+and $\sigma_{\epsilon}$ is the standard deviation of the error in predicting
+the outcome, $y$. The likelihood of the entire sample is the product of $N$
+individual likelihood contributions.
+
+It is well-known that the likelihood of the sample is maximized when the 
+sum-of-squared residuals is minimized, which occurs when
+$$ \widehat{\boldsymbol{\beta}} = \left(\mathbf{X}^\top \mathbf{X}\right)^{-1}
+                                   \mathbf{X}^\top \mathbf{y}, $$
+$$ \widehat{\alpha} = \overline{y} - \overline{\mathbf{x}}^\top 
+                                     \widehat{\boldsymbol{\beta}}, $$
+$$ \widehat{\sigma}_{\epsilon}^2 = 
+  \frac{\left(\mathbf{y} - \widehat{\alpha} - \mathbf{X} \widehat{
+                                              \boldsymbol{\beta}}\right)^\top
+        \left(\mathbf{y} - \widehat{\alpha} - \mathbf{X} \widehat{
+                                              \boldsymbol{\beta}}\right)}{N},$$
+where $\overline{\mathbf{x}}$ is a vector that contains the sample means of the
+$K$ predictors, $\mathbf{X}$ is a $N \times K$ matrix of _centered_ predictors, 
+$\mathbf{y}$ is a $N$-vector of outcomes and $\overline{y}$ is the sample mean 
+of the outcome.
+
+Boldsymbol should render, i.e. this should render properly: $\boldsymbol{\beta}$ and not error out.