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man/gamlss2.html

@@ -629,7 +629,7 @@ <h3 class="anchored" data-anchor-id="examples">Examples</h3>
 *--------
 n = 610 df =  13.12 res.df =  596.88
 Deviance = 4770.1554 Null Dev. Red. = 33.39%
-AIC = 4796.3966 elapsed =  0.79sec</code></pre>
+AIC = 4796.3966 elapsed =  0.78sec</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb5"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" aria-hidden="true" tabindex="-1"></a><span class="do">## plot estimated effects</span></span>
 <span id="cb5-2"><a href="#cb5-2" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(b, <span class="at">which =</span> <span class="st">"effects"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>

man/prodist.gamlss2.html

@@ -537,10 +537,10 @@ <h3 class="anchored" data-anchor-id="examples">Examples</h3>
 <div class="sourceCode cell-code" id="cb16"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb16-1"><a href="#cb16-1" aria-hidden="true" tabindex="-1"></a><span class="do">## simulate random numbers</span></span>
 <span id="cb16-2"><a href="#cb16-2" aria-hidden="true" tabindex="-1"></a><span class="fu">random</span>(d, <span class="dv">5</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
 <div class="cell-output cell-output-stdout">
-<pre><code>        r_1      r_2      r_3       r_4       r_5
-1  31.05780 21.75938 38.72207  30.45697  7.291457
-2  72.34082 55.52784 90.11789  55.03528 50.178667
-3 156.37972 52.94278 71.96659 105.99172 91.297804</code></pre>
+<pre><code>        r_1       r_2       r_3      r_4       r_5
+1  49.46417  43.74521  15.64832 16.14411  24.40045
+2  48.73735  39.49597  28.76521 60.20798  32.97853
+3 135.79246 117.37999 118.64879 92.26730 100.15979</code></pre>
 </div>
 <div class="sourceCode cell-code" id="cb18"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" aria-hidden="true" tabindex="-1"></a><span class="do">## density and distribution</span></span>
 <span id="cb18-2"><a href="#cb18-2" aria-hidden="true" tabindex="-1"></a><span class="fu">pdf</span>(d, <span class="dv">50</span> <span class="sc">*</span> <span class="sc">-</span><span class="dv">2</span><span class="sc">:</span><span class="dv">2</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>

vignettes/families.html

@@ -561,7 +561,7 @@ <h2 data-number="4" class="anchored" data-anchor-id="additional-functions"><span
 <li>Random number generation (<code>r()</code>).</li>
 </ul>
 <p>These functions should adhere to the same structure as the density function, taking the response (<code>y</code>), parameters (<code>par</code>), and other relevant arguments.</p>
-<p>Note that the CDF <code>q()</code> function is mandatory for computing quantile residuals.</p>
+<p>Note that the CDF <code>p()</code> function is mandatory for computing quantile residuals.</p>
 </section>
 <section id="flexible-links" class="level2" data-number="5">
 <h2 data-number="5" class="anchored" data-anchor-id="flexible-links"><span class="header-section-number">5</span> Flexible Links</h2>

vignettes/mixture.html

@@ -518,7 +518,7 @@ <h2 data-number="3" class="anchored" data-anchor-id="gamlss-framework-for-the-mi
 </section>
 <section id="example-using-simulated-data" class="level2" data-number="4">
 <h2 data-number="4" class="anchored" data-anchor-id="example-using-simulated-data"><span class="header-section-number">4</span> Example using Simulated Data</h2>
-<p>We begin by simulating data where the response <code>y</code> is generated by one of two normal distributions, depending on a covariate <code>x</code>. The latent component membership is determined by a logistic model.</p>
+<p>We begin by simulating data where the response <code>y</code> is generated by one of two normal distributions, depending on a covariate <code>x</code>. The latent component membership is determined by a logistic model. Morover, we let the standard deviation of the first component also depend on <code>x</code>.</p>
 <div class="cell" data-layout-align="center">
 <div class="sourceCode cell-code" id="cb1"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" aria-hidden="true" tabindex="-1"></a><span class="fu">set.seed</span>(<span class="dv">123</span>)</span>
 <span id="cb1-2"><a href="#cb1-2" aria-hidden="true" tabindex="-1"></a></span>