rendering for final workshop materials

docs/GP_Solutions.html

@@ -254,7 +254,7 @@ <h5 class="anchored" data-anchor-id="challenges">Challenges</h5>
 <div class="sourceCode cell-code" id="cb6"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" aria-hidden="true" tabindex="-1"></a><span class="co"># Pulling the data from the NEON data base. </span></span>
 <span id="cb6-2"><a href="#cb6-2" aria-hidden="true" tabindex="-1"></a>target <span class="ot">&lt;-</span> readr<span class="sc">::</span><span class="fu">read_csv</span>(<span class="st">"https://data.ecoforecast.org/neon4cast-targets/ticks/ticks-targets.csv.gz"</span>, <span class="at">guess_max =</span> <span class="fl">1e1</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>Rows: 587 Columns: 5
+<pre><code>Rows: 601 Columns: 5
 ── Column specification ────────────────────────────────────────────────────────
 Delimiter: ","
 chr  (3): site_id, variable, iso_week
@@ -756,8 +756,8 @@ <h6 class="anchored" data-anchor-id="fit-a-gp-model-for-all-the-locations-more-a
 OSBS 1.2057049
 SCBI 0.8610973
 SERC 0.9532001
-TALL 1.0072034
-UKFS 1.5292849</code></pre>
+TALL 0.8883320
+UKFS 0.9521605</code></pre>
 </div>
 </div>
 

docs/Stats_review.html

@@ -353,7 +353,7 @@ <h1>Random Variables (RVs)</h1>
 <li>discrete (numbers of items or successes)</li>
 <li>continuous (heights, times, weights)</li>
 </ul>
-<p>We usually use capital letters – e.g.&nbsp;<span class="math inline">X</span>, <span class="math inline">Y</span>, sometimes with bold or with subscripts – to denote the RVs. In contrast we use lower case letters, e.g.&nbsp;<span class="math inline">x</span>, <span class="math inline">y</span>, <span class="math inline">k</span>, to denote the values that the RV takes. For instance, lets say that the heights of the woman at Virginia Tech are the RV, <span class="math inline">X</span>, and <span class="math inline">X</span> has a normal distribution with mean 62 inches and variance 6<span class="math inline">^2</span>, i.e., <span class="math inline">X \sim \mathrm{N}(62,6^2)</span> distribution. Say we then observe the heights of 3 individuals drawn from this distribution – we would write this as: <span class="math inline">x=(</span> 62.7, 55.2, 59.3 <span class="math inline">)</span>.</p>
+<p>We usually use capital letters – e.g.&nbsp;<span class="math inline">X</span>, <span class="math inline">Y</span>, sometimes with bold or with subscripts – to denote the RVs. In contrast we use lower case letters, e.g.&nbsp;<span class="math inline">x</span>, <span class="math inline">y</span>, <span class="math inline">k</span>, to denote the values that the RV takes. For instance, lets say that the heights of the woman at Virginia Tech are the RV, <span class="math inline">X</span>, and <span class="math inline">X</span> has a normal distribution with mean 62 inches and variance 6<span class="math inline">^2</span>, i.e., <span class="math inline">X \sim \mathrm{N}(62,6^2)</span> distribution. Say we then observe the heights of 3 individuals drawn from this distribution – we would write this as: <span class="math inline">x=(</span> 60.3, 62.9, 63.8 <span class="math inline">)</span>.</p>
 <p><br> <br> </p>
 </section>
 <section id="probability-distributions" class="level1">
@@ -577,7 +577,7 @@ <h1>Probability Distributions in <code>R</code></h1>
 <div class="cell">
 <div class="sourceCode cell-code" id="cb3"><pre class="sourceCode r code-with-copy"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" aria-hidden="true" tabindex="-1"></a><span class="fu">rnorm</span>(<span class="dv">3</span>, <span class="at">mean=</span><span class="dv">0</span>, <span class="at">sd=</span><span class="dv">1</span>) <span class="do">## random draws</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>[1]  0.1637976  0.1531684 -2.5787919</code></pre>
+<pre><code>[1] 1.410971 1.186608 0.194505</code></pre>
 </div>
 </div>
 <div class="cell">

docs/index.html

@@ -149,7 +149,7 @@ <h1 class="title">Welcome to the 2024 VectorByte Training Workshop</h1>
 </header>
 
 
-<p><strong><em>Check out our <a href="./about.html">about</a> and <a href="">schedule: coming soon!</a> pages to continue.</em></strong></p>
+<p><strong><em>Check out our <a href="./about.html">about</a> and <a href="./schedule2024.html">schedule</a> pages to continue.</em></strong></p>
 <p>Information about pre-workshop preparation – including software installation, expectations for what you should already be familiar with, and review materials – is available in the <a href="materials.html#pre-work-and-set-up">pre-work portion of the materials page</a>.</p>
 <p><br> <br> <br></p>
 <center>

docs/materials.html

@@ -137,11 +137,11 @@ <h2 id="toc-title">On this page</h2>
   </ul></li>
   <li><a href="#live-workshop-materials" id="toc-live-workshop-materials" class="nav-link" data-scroll-target="#live-workshop-materials">Live Workshop Materials</a>
   <ul class="collapse">
-  <li><a href="#introduction-to-time-dependent-abundance-data" id="toc-introduction-to-time-dependent-abundance-data" class="nav-link" data-scroll-target="#introduction-to-time-dependent-abundance-data">Introduction to Time Dependent Abundance Data</a></li>
-  <li><a href="#introduction-to-the-vecdyn-database1" id="toc-introduction-to-the-vecdyn-database1" class="nav-link" data-scroll-target="#introduction-to-the-vecdyn-database1">Introduction to the VecDyn database</a></li>
-  <li><a href="#regression-in-r-refresher" id="toc-regression-in-r-refresher" class="nav-link" data-scroll-target="#regression-in-r-refresher">Regression in R Refresher</a></li>
+  <li><a href="#introduction-to-the-workshop" id="toc-introduction-to-the-workshop" class="nav-link" data-scroll-target="#introduction-to-the-workshop">Introduction to the Workshop</a></li>
+  <li><a href="#regression-in-r-refresher-transformations-and-diagnostics" id="toc-regression-in-r-refresher-transformations-and-diagnostics" class="nav-link" data-scroll-target="#regression-in-r-refresher-transformations-and-diagnostics">Regression in R Refresher (Transformations and Diagnostics)</a></li>
   <li><a href="#time-dependent-regression-analysis" id="toc-time-dependent-regression-analysis" class="nav-link" data-scroll-target="#time-dependent-regression-analysis">Time dependent regression analysis</a></li>
-  <li><a href="#basics-of-time-series-using-r" id="toc-basics-of-time-series-using-r" class="nav-link" data-scroll-target="#basics-of-time-series-using-r">Basics of Time Series using R</a></li>
+  <li><a href="#basics-of-forecasting-time-series-using-r" id="toc-basics-of-forecasting-time-series-using-r" class="nav-link" data-scroll-target="#basics-of-forecasting-time-series-using-r">Basics of Forecasting Time Series using R</a></li>
+  <li><a href="#introduction-to-the-vecdyn-database" id="toc-introduction-to-the-vecdyn-database" class="nav-link" data-scroll-target="#introduction-to-the-vecdyn-database">Introduction to the VecDyn database</a></li>
   <li><a href="#gaussian-process-models-gps-for-time-dependent-data" id="toc-gaussian-process-models-gps-for-time-dependent-data" class="nav-link" data-scroll-target="#gaussian-process-models-gps-for-time-dependent-data">Gaussian Process models (GPs) for Time Dependent Data</a></li>
   </ul></li>
   </ul>
@@ -199,44 +199,70 @@ <h2 class="anchored" data-anchor-id="pre-requisites">Pre-requisites</h2>
 </section>
 <section id="live-workshop-materials" class="level1">
 <h1>Live Workshop Materials</h1>
-<section id="introduction-to-time-dependent-abundance-data" class="level2">
-<h2 class="anchored" data-anchor-id="introduction-to-time-dependent-abundance-data">Introduction to Time Dependent Abundance Data</h2>
-<p><br> <br></p>
-</section>
-<section id="introduction-to-the-vecdyn-database1" class="level2">
-<h2 class="anchored" data-anchor-id="introduction-to-the-vecdyn-database1">Introduction to the VecDyn database<a href="#fn1" class="footnote-ref" id="fnref1" role="doc-noteref"><sup>1</sup></a></h2>
+<section id="introduction-to-the-workshop" class="level2">
+<h2 class="anchored" data-anchor-id="introduction-to-the-workshop">Introduction to the Workshop</h2>
 <ul>
-<li>This component will be delivered live &amp; synchronously. The VecDyn website can be found <a href="https://vectorbyte.crc.nd.edu/vecdyn-datasets">here</a>. It might be an idea to explore this prior to the workshop.</li>
+<li><a href="./VB_IntroTimeDepData.html">Lecture</a></li>
 </ul>
 <p><br> <br></p>
 </section>
-<section id="regression-in-r-refresher" class="level2">
-<h2 class="anchored" data-anchor-id="regression-in-r-refresher">Regression in R Refresher</h2>
+<section id="regression-in-r-refresher-transformations-and-diagnostics" class="level2">
+<h2 class="anchored" data-anchor-id="regression-in-r-refresher-transformations-and-diagnostics">Regression in R Refresher (Transformations and Diagnostics)</h2>
+<ul>
+<li><a href="./VB_RegDiagTrans.html">Lecture Slides</a></li>
+<li><a href="./VB_RegDiagTrans_practical.html">Practical</a></li>
+<li>Dataset: <a href="./data/transforms.csv">transforms.csv</a></li>
+</ul>
 <p><br> <br></p>
 </section>
 <section id="time-dependent-regression-analysis" class="level2">
 <h2 class="anchored" data-anchor-id="time-dependent-regression-analysis">Time dependent regression analysis</h2>
+<ul>
+<li><a href="./VB_TimeDepData.html">Lecture Slides</a></li>
+<li><a href="./VB_TimeDepData_practical.html">Practical</a></li>
+<li>Dataset: <a href="./data/Culex_erraticus_walton_covariates_aggregated.csv">Walton Co, FL Mosquito data</a></li>
+</ul>
+<p><br> <br></p>
+</section>
+<section id="basics-of-forecasting-time-series-using-r" class="level2">
+<h2 class="anchored" data-anchor-id="basics-of-forecasting-time-series-using-r">Basics of Forecasting Time Series using R</h2>
+<ul>
+<li><a href="VB_TimeSeriesBasicsR_Lecture.pdf">Lecture</a></li>
+<li><a href="./VB_TimeSeriesForecastingPractical.html">Practical</a></li>
+<li>Datasets:
+<ul>
+<li><a href="data/NEONphenologyClean.csv">NEONphenologyClean.csv</a></li>
+<li><a href="data/phenologyWeather.csv">phenologyWeather.csv</a></li>
+<li><a href="data/NEONbeetlesChallenge.csv">NEONbeetlesChallenge.csv</a></li>
+<li><a href="data/tinyForecastingChallengeCovs.csv">tinyForecastingChallengeCovs.csv</a></li>
+</ul></li>
+</ul>
 <p><br> <br></p>
 </section>
-<section id="basics-of-time-series-using-r" class="level2">
-<h2 class="anchored" data-anchor-id="basics-of-time-series-using-r">Basics of Time Series using R</h2>
+<section id="introduction-to-the-vecdyn-database" class="level2">
+<h2 class="anchored" data-anchor-id="introduction-to-the-vecdyn-database">Introduction to the VecDyn database</h2>
+<ul>
+<li><a href="https://vectorbyte.crc.nd.edu/vecdyn-datasets">The VecDyn website</a>.</li>
+<li><a href="https://www.vectorbyte.org/blog/vecdyn-api">About the VecDyn API</a></li>
+<li>Other Materials Coming Soon!</li>
+</ul>
 <p><br> <br></p>
 </section>
 <section id="gaussian-process-models-gps-for-time-dependent-data" class="level2">
 <h2 class="anchored" data-anchor-id="gaussian-process-models-gps-for-time-dependent-data">Gaussian Process models (GPs) for Time Dependent Data</h2>
+<ul>
+<li><a href="./GP.html">Lecture Slides</a></li>
+<li><a href="./GP_Notes.html">Lecture Notes</a></li>
+<li><a href="./GP_Practical.html">Practical</a></li>
+<li><a href="code/df_spline.R">additional R code – df_spline.R</a></li>
+</ul>
 <p><br> <br></p>
 
 
 </section>
 </section>
 
-
-<div id="quarto-appendix" class="default"><section id="footnotes" class="footnotes footnotes-end-of-document" role="doc-endnotes"><h2 class="anchored quarto-appendix-heading">Footnotes</h2>
-
-<ol>
-<li id="fn1"><p>What is the difference between VectorBiTE and VectorByte? We are glad you asked! <a href="http://vectorbite.org/">VectorBiTE</a> was an RCN or a research coordination network funded by a 5 year grant from the BBSRC. <a href="https://www.vectorbyte.org/">VectorByte</a> is hosting this training which is a newly funded NSF grant to establish a global open access data platform to study disease vectors. All the databases have transitioned to VectorByte but the legacy options will still be available on the VectorBiTE website.<a href="#fnref1" class="footnote-back" role="doc-backlink">↩︎</a></p></li>
-</ol>
-</section></div></main> <!-- /main -->
+</main> <!-- /main -->
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