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Refereed to readme & update htmls
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‎docs/index.html

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<!DOCTYPE html>
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<meta name="author" content="by Valentin Stefan - last update 11 December 2019" />
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<meta name="author" content="by Valentin Stefan - last update 30 May 2024" />
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<title>bootstrapnet - R package to bootstrap indices of ecological networks</title>
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<h1 class="title toc-ignore">bootstrapnet - R package to bootstrap indices of ecological networks</h1>
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<h4 class="author">by <a href="https://github.com/valentinitnelav">Valentin Stefan</a> - last update 11 December 2019</h4>
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<h1 class="title toc-ignore">bootstrapnet - R package to bootstrap
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indices of ecological networks</h1>
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<h4 class="author">by <a
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href="https://github.com/valentinitnelav">Valentin Stefan</a> - last
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update 30 May 2024</h4>
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<div id="overview" class="section level1">
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<h1>Overview</h1>
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<p>R package for resampling network metrics/indices (bootstrapping without replacement).</p>
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<p>It wraps around the <a href="https://cran.r-project.org/web/packages/bipartite/index.html">bipartite</a> package functions <code>networklevel</code> and <code>specieslevel</code>.</p>
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<p>Assuming a network/web like <code>Safariland</code> from the bipartite package:</p>
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<p>R package for resampling network metrics/indices (bootstrapping
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without replacement).</p>
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<p>It wraps around the <a
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href="https://cran.r-project.org/web/packages/bipartite/index.html">bipartite</a>
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package functions <code>networklevel</code> and
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<code>specieslevel</code>.</p>
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<p>Assuming a network/web like <code>Safariland</code> from the
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bipartite package:</p>
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<pre class="r"><code>library(bipartite)
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data(Safariland)</code></pre>
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<p>One can sample interactions without replacement from the network until all interactions have been used. The sampling procedure starts with a small sample size to which interactions are added until all are consumed. Every time we sample interactions, a smaller version of the entire network can be built and a network index/metric can be computed. The sampling procedure can be repeated as many times as needed, giving the possibility to compute mean values with quantile-based confidence intervals. The mean values across sample sizes can be plotted and indices of different networks can be visually compared. See examples below.</p>
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<p>Below is an animation of the sampling method (one iteration). A detailed explanation of the method can be found <a href="https://valentinitnelav.github.io/bootstrapnet/explain-sampling-method.html">here</a>.</p>
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<p><img src="https://github.com/valentinitnelav/bootstrapnet/raw/master/man/cache/sample-nestedness-1-boot.gif" /></p>
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<p>One can sample interactions without replacement from the network
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until all interactions have been used. The sampling procedure starts
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with a small sample size to which interactions are added until all are
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consumed. Every time we sample interactions, a smaller version of the
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entire network can be built and a network index/metric can be computed.
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The sampling procedure can be repeated as many times as needed, giving
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the possibility to compute mean values with quantile-based confidence
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intervals. The mean values across sample sizes can be plotted and
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indices of different networks can be visually compared. See examples
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below.</p>
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<p>Below is an animation of the sampling method (one iteration). A
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detailed explanation of the method can be found <a
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href="https://valentinitnelav.github.io/bootstrapnet/explain-sampling-method.html">here</a>.</p>
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<p><img
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src="https://github.com/valentinitnelav/bootstrapnet/raw/master/man/cache/sample-nestedness-1-boot.gif" /></p>
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<p>See also the <a
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href="https://github.com/valentinitnelav/bootstrapnet?tab=readme-ov-file#overview">README
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file</a> on the GitHub code base.</p>
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<div id="installation" class="section level1">
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<h1>Installation</h1>
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<p>You can install <code>bootstrapnet</code> from GitHub with:</p>
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<pre class="r"><code># install.packages(&quot;devtools&quot;)
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devtools::install_github(&quot;valentinitnelav/bootstrapnet&quot;)</code></pre>
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<p>See details in the <a
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href="https://github.com/valentinitnelav/bootstrapnet?tab=readme-ov-file#installation">README
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