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authorJohannes Ranke <jranke@uni-bremen.de>2019-10-21 22:46:33 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2019-10-21 22:46:33 +0200
commitaed80b602afbe8c22ba601bf236dda22bc39187c (patch)
tree1fc6bed5a29a8e75bf9e8fec6ae70b1d93f8c127 /docs/reference/synthetic_data_for_UBA_2014.html
parent5b711837e28d838f20c67c057d8de36f3927ff65 (diff)
Static documentation rebuilt by pkgdown
Diffstat (limited to 'docs/reference/synthetic_data_for_UBA_2014.html')
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diff --git a/docs/reference/synthetic_data_for_UBA_2014.html b/docs/reference/synthetic_data_for_UBA_2014.html
index ddc88c21..f23b77b0 100644
--- a/docs/reference/synthetic_data_for_UBA_2014.html
+++ b/docs/reference/synthetic_data_for_UBA_2014.html
@@ -8,11 +8,13 @@
<title>Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • mkin</title>
+
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<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js" integrity="sha256-FgpCb/KJQlLNfOu91ta32o/NMZxltwRo8QtmkMRdAu8=" crossorigin="anonymous"></script>
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@@ -32,8 +34,8 @@
-<meta property="og:title" content="Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014" />
+<meta property="og:title" content="Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014" />
<meta property="og:description" content="The 12 datasets were generated using four different models and three different
variance components. The four models are either the SFO or the DFOP model with either
two sequential or two parallel metabolites.
@@ -54,6 +56,7 @@ Compare also the code in the example section to see the degradation models." />
+
<!-- mathjax -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script>
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@@ -124,7 +127,6 @@ Compare also the code in the example section to see the degradation models." />
<a href="../news/index.html">News</a>
</li>
</ul>
-
<ul class="nav navbar-nav navbar-right">
</ul>
@@ -146,7 +148,6 @@ Compare also the code in the example section to see the degradation models." />
</div>
<div class="ref-description">
-
<p>The 12 datasets were generated using four different models and three different
variance components. The four models are either the SFO or the DFOP model with either
two sequential or two parallel metabolites.</p>
@@ -163,11 +164,11 @@ Compare also the code in the example section to see the degradation models." />
<p>As an example, the first dataset has the title <code>SFO_lin_a</code> and is based on the SFO model
with two sequential metabolites (linear pathway), with added variance component 'a'.</p>
<p>Compare also the code in the example section to see the degradation models.</p>
-
</div>
<pre class="usage"><span class='no'>synthetic_data_for_UBA_2014</span></pre>
-
+
+
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A list containing twelve datasets as an R6 class defined by <code><a href='mkinds.html'>mkinds</a></code>,
@@ -177,17 +178,16 @@ Compare also the code in the example section to see the degradation models." />
</dl>
-
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452</p>
<p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
-
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
- <pre class="examples"><div class='input'><span class='co'># The data have been generated using the following kinetic models</span>
+ <pre class="examples"><div class='input'><span class='co'># \dontrun{</span>
+<span class='co'># The data have been generated using the following kinetic models</span>
<span class='no'>m_synth_SFO_lin</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M1"</span>),
<span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"M2"</span>),
<span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
@@ -249,7 +249,7 @@ Compare also the code in the example section to see the degradation models." />
<span class='co'># d_rep = data.frame(lapply(d_long, rep, each = 2))</span>
<span class='co'># d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))</span>
<span class='co'>#</span>
-<span class='co'># d_rep[d_rep$time == 0 &amp; d_rep$name %in% c("M1", "M2"), "value"] &lt;- 0</span>
+<span class='co'># d_rep[d_rep$time == 0 &amp; d_rep$name </span>
<span class='co'># d_NA &lt;- transform(d_rep, value = ifelse(value &lt; LOD, NA, value))</span>
<span class='co'># d_NA$value &lt;- round(d_NA$value, 1)</span>
<span class='co'># return(d_NA)</span>
@@ -278,13 +278,12 @@ Compare also the code in the example section to see the degradation models." />
<span class='co'># This is just one example of an evaluation using the kinetic model used for</span>
<span class='co'># the generation of the data</span>
-<span class='co'># \dontrun{</span>
<span class='no'>fit</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_synth_SFO_lin</span>, <span class='no'>synthetic_data_for_UBA_2014</span><span class='kw'>[[</span><span class='fl'>1</span>]]$<span class='no'>data</span>,
<span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>fit</span>)</div><div class='img'><img src='synthetic_data_for_UBA_2014-1.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>fit</span>)</div><div class='output co'>#&gt; mkin version used for fitting: 0.9.49.6
#&gt; R version used for fitting: 3.6.1
-#&gt; Date of fit: Mon Oct 21 18:52:20 2019
-#&gt; Date of summary: Mon Oct 21 18:52:20 2019
+#&gt; Date of fit: Mon Oct 21 22:46:31 2019
+#&gt; Date of summary: Mon Oct 21 22:46:31 2019
#&gt;
#&gt; Equations:
#&gt; d_parent/dt = - k_parent * parent
@@ -293,7 +292,7 @@ Compare also the code in the example section to see the degradation models." />
#&gt;
#&gt; Model predictions using solution type deSolve
#&gt;
-#&gt; Fitted using 847 model solutions performed in 2.42 s
+#&gt; Fitted using 847 model solutions performed in 2.45 s
#&gt;
#&gt; Error model: Constant variance
#&gt;
@@ -429,11 +428,8 @@ Compare also the code in the example section to see the degradation models." />
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
-
<li><a href="#format">Format</a></li>
-
<li><a href="#source">Source</a></li>
-
<li><a href="#examples">Examples</a></li>
</ul>

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