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2 changes: 1 addition & 1 deletion .nojekyll
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<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">

<meta name="dcterms.date" content="2024-08-27">
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<title>Bayesian Data Analysis course - Aalto 2023 – Bayesian Data Analysis course</title>
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<div class="quarto-title-meta-heading">Published</div>
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<p class="date">August 29, 2024</p>
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<title>Bayesian Data Analysis course - Aalto 2024 – Bayesian Data Analysis course</title>
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<title>Bayesian Data Analysis course - BDA3 notes – Bayesian Data Analysis course</title>
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<div class="quarto-title-meta-heading">Published</div>
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<title>Bayesian Data Analysis course - FAQ – Bayesian Data Analysis course</title>
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<p class="date">August 27, 2024</p>
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<title>Bayesian Data Analysis course - Assignments – Bayesian Data Analysis course</title>
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<p class="date">August 27, 2024</p>
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</div>
<div class="sourceCode cell-code" id="cb64"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb64-1"><a href="#cb64-1"></a>loo_f3 <span class="ot">&lt;-</span> <span class="fu">loo</span>(f3)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: Found 1 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
<pre><code>Warning: Found 3 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
to set 'moment_match = TRUE' in order to perform moment matching for
problematic observations.</code></pre>
</div>
Expand All @@ -1233,17 +1233,17 @@ <h2 data-number="2.5" class="anchored" data-anchor-id="model-comparison-using-th
Computed from 4000 by 578 log-likelihood matrix.

Estimate SE
elpd_loo -2253.2 27.0
p_loo 76.9 6.4
looic 4506.4 54.1
elpd_loo -2254.2 27.1
p_loo 77.8 6.6
looic 4508.3 54.2
------
MCSE of elpd_loo is NA.
MCSE and ESS estimates assume MCMC draws (r_eff in [0.3, 1.4]).
MCSE and ESS estimates assume MCMC draws (r_eff in [0.4, 1.6]).

Pareto k diagnostic values:
Count Pct. Min. ESS
(-Inf, 0.7] (good) 577 99.8% 129
(0.7, 1] (bad) 1 0.2% &lt;NA&gt;
(-Inf, 0.7] (good) 575 99.5% 106
(0.7, 1] (bad) 3 0.5% &lt;NA&gt;
(1, Inf) (very bad) 0 0.0% &lt;NA&gt;
See help('pareto-k-diagnostic') for details.</code></pre>
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Expand Down Expand Up @@ -1311,7 +1311,7 @@ <h2 data-number="2.5" class="anchored" data-anchor-id="model-comparison-using-th
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<div class="sourceCode cell-code" id="cb75"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb75-1"><a href="#cb75-1"></a><span class="fu">plot</span>(<span class="fu">loo</span>(f3), <span class="at">label_points =</span> <span class="cn">TRUE</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-stderr">
<pre><code>Warning: Found 1 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
<pre><code>Warning: Found 3 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
to set 'moment_match = TRUE' in order to perform moment matching for
problematic observations.</code></pre>
</div>
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Mean chain execution time: 28.9 seconds.
Total execution time: 35.3 seconds.</code></pre>
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<div class="cell-output cell-output-stderr">
<pre><code>Warning: 288 of 1000 (29.0%) transitions ended with a divergence.
<pre><code>Warning: 271 of 1000 (27.0%) transitions ended with a divergence.
See https://mc-stan.org/misc/warnings for details.</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: 629 of 1000 (63.0%) transitions hit the maximum treedepth limit of 10.
<pre><code>Warning: 602 of 1000 (60.0%) transitions hit the maximum treedepth limit of 10.
See https://mc-stan.org/misc/warnings for details.</code></pre>
</div>
<div class="sourceCode cell-code" id="cb36"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb36-1"><a href="#cb36-1"></a>brms<span class="sc">::</span><span class="fu">pp_check</span>(fit, <span class="at">type =</span> <span class="st">"intervals_grouped"</span>, <span class="at">group =</span> <span class="st">"Diet"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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Expand Down Expand Up @@ -1223,7 +1223,7 @@ <h2 data-number="2.5" class="anchored" data-anchor-id="model-comparison-using-th
</div>
<div class="sourceCode cell-code" id="cb64"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb64-1"><a href="#cb64-1"></a>loo_f3 <span class="ot">&lt;-</span> <span class="fu">loo</span>(f3)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: Found 5 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
<pre><code>Warning: Found 4 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
to set 'moment_match = TRUE' in order to perform moment matching for
problematic observations.</code></pre>
</div>
Expand All @@ -1233,17 +1233,17 @@ <h2 data-number="2.5" class="anchored" data-anchor-id="model-comparison-using-th
Computed from 4000 by 578 log-likelihood matrix.

Estimate SE
elpd_loo -2252.8 26.9
p_loo 77.4 6.5
looic 4505.7 53.9
elpd_loo -2253.8 27.1
p_loo 77.5 6.6
looic 4507.5 54.2
------
MCSE of elpd_loo is NA.
MCSE and ESS estimates assume MCMC draws (r_eff in [0.4, 1.5]).
MCSE and ESS estimates assume MCMC draws (r_eff in [0.3, 1.5]).

Pareto k diagnostic values:
Count Pct. Min. ESS
(-Inf, 0.7] (good) 573 99.1% 209
(0.7, 1] (bad) 5 0.9% &lt;NA&gt;
(-Inf, 0.7] (good) 574 99.3% 85
(0.7, 1] (bad) 4 0.7% &lt;NA&gt;
(1, Inf) (very bad) 0 0.0% &lt;NA&gt;
See help('pareto-k-diagnostic') for details.</code></pre>
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Expand Down Expand Up @@ -1311,7 +1311,7 @@ <h2 data-number="2.5" class="anchored" data-anchor-id="model-comparison-using-th
</div>
<div class="sourceCode cell-code" id="cb75"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb75-1"><a href="#cb75-1"></a><span class="fu">plot</span>(<span class="fu">loo</span>(f3), <span class="at">label_points =</span> <span class="cn">TRUE</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-stderr">
<pre><code>Warning: Found 5 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
<pre><code>Warning: Found 4 observations with a pareto_k &gt; 0.7 in model 'f3'. We recommend
to set 'moment_match = TRUE' in order to perform moment matching for
problematic observations.</code></pre>
</div>
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Total execution time: 39.1 seconds.</code></pre>
Mean chain execution time: 40.3 seconds.
Total execution time: 41.0 seconds.</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: 49 of 1000 (5.0%) transitions ended with a divergence.
<pre><code>Warning: 16 of 1000 (2.0%) transitions ended with a divergence.
See https://mc-stan.org/misc/warnings for details.</code></pre>
</div>
<div class="cell-output cell-output-stderr">
<pre><code>Warning: 817 of 1000 (82.0%) transitions hit the maximum treedepth limit of 10.
<pre><code>Warning: 944 of 1000 (94.0%) transitions hit the maximum treedepth limit of 10.
See https://mc-stan.org/misc/warnings for details.</code></pre>
</div>
<div class="sourceCode cell-code" id="cb36"><pre class="sourceCode numberSource r number-lines code-with-copy"><code class="sourceCode r"><span id="cb36-1"><a href="#cb36-1"></a>brms<span class="sc">::</span><span class="fu">pp_check</span>(fit, <span class="at">type =</span> <span class="st">"intervals_grouped"</span>, <span class="at">group =</span> <span class="st">"Diet"</span>)</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
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