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authorJohannes Ranke <jranke@uni-bremen.de>2017-05-05 12:46:31 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2017-05-05 12:46:31 +0200
commitccc70e82af4ba435f0a71ba1ae4e0e92045c3852 (patch)
treed8ffd99be771f47eae876f244b049742481bdd25 /docs/reference/synthetic_data_for_UBA.html
parent1c7dbeec335c404377381157d34db6e219ce3f21 (diff)
Static docs except articles rebuilt with current pkgdown
Diffstat (limited to 'docs/reference/synthetic_data_for_UBA.html')
-rw-r--r--docs/reference/synthetic_data_for_UBA.html83
1 files changed, 43 insertions, 40 deletions
diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html
index bc2bb02b..d8ff3a1e 100644
--- a/docs/reference/synthetic_data_for_UBA.html
+++ b/docs/reference/synthetic_data_for_UBA.html
@@ -25,12 +25,14 @@
<script src="../pkgdown.js"></script>
<!-- mathjax -->
-<script src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></script>
+<script src='https://mathjax.rstudio.com/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></script>
<!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]-->
+
+
</head>
<body>
@@ -70,8 +72,14 @@
<li>
<a href="../articles/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a>
</li>
+ <li>
+ <a href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a>
+ </li>
</ul>
</li>
+<li>
+ <a href="../news/index.html">News</a>
+</li>
</ul>
<ul class="nav navbar-nav navbar-right">
@@ -99,39 +107,34 @@
<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>
-
- <p>Variance component &#39;a&#39; is based on a normal distribution with standard deviation of 3,
- Variance component &#39;b&#39; is also based on a normal distribution, but with a standard deviation of 7.
- Variance component &#39;c&#39; is based on the error model from Rocke and Lorenzato (1995), with the
+<p>Variance component 'a' is based on a normal distribution with standard deviation of 3,
+ Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
+ Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
for the increase of the standard deviation with y.</p>
-
- <p>Initial concentrations for metabolites and all values where adding the variance component resulted
+<p>Initial concentrations for metabolites and all values where adding the variance component resulted
in a value below the assumed limit of detection of 0.1 were set to <code>NA</code>.</p>
-
- <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 &#39;a&#39;.</p>
-
- <p>Compare also the code in the example section to see the degradation models.</p>
+<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>
- <pre><span class='no'>synthetic_data_for_UBA_2014</span></pre>
+ <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 datasets in the form internally used by the &#39;gmkin&#39; package.
+ <p>A list containing datasets in the form internally used by the 'gmkin' package.
The list has twelfe components. Each of the components is one dataset that has,
- among others, the following components
- <dl class='dl-horizontal'>
- <dt><code>title</code></dt><dd>The name of the dataset, e.g. <code>SFO_lin_a</code></dd>
- <dt><code>data</code></dt><dd>A data frame with the data in the form expected by <code><a href='mkinfit.html'>mkinfit</a></code></dd>
- </dl></p>
+ among others, the following components</p><dl class='dl-horizontal'>
+ <dt><code>title</code></dt><dd><p>The name of the dataset, e.g. <code>SFO_lin_a</code></p></dd>
+ <dt><code>data</code></dt><dd><p>A data frame with the data in the form expected by <code><a href='mkinfit.html'>mkinfit</a></code></p></dd>
+ </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
+ zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452
+ Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
@@ -153,10 +156,10 @@
<span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>),
<span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'>list</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'>
<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><img src='synthetic_data_for_UBA_2014-10.png' alt='' width='540' height='400' /><div class='input'><span class='fu'>summary</span>(<span class='no'>fit</span>)</div><div class='output co'>#&gt; mkin version: 0.9.44.9000
-#&gt; R version: 3.3.2
-#&gt; Date of fit: Thu Dec 8 07:57:58 2016
-#&gt; Date of summary: Thu Dec 8 07:57:58 2016
+<span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>fit</span>)</div><img src='synthetic_data_for_UBA_2014-10.png' alt='' width='540' height='400' /><div class='input'><span class='fu'>summary</span>(<span class='no'>fit</span>)</div><div class='output co'>#&gt; mkin version: 0.9.45.2
+#&gt; R version: 3.4.0
+#&gt; Date of fit: Fri May 5 12:46:23 2017
+#&gt; Date of summary: Fri May 5 12:46:23 2017
#&gt;
#&gt; Equations:
#&gt; d_parent/dt = - k_parent * parent
@@ -165,7 +168,7 @@
#&gt;
#&gt; Model predictions using solution type deSolve
#&gt;
-#&gt; Fitted with method Port using 351 model solutions performed in 2.152 s
+#&gt; Fitted with method Port using 381 model solutions performed in 2.203 s
#&gt;
#&gt; Weighting: none
#&gt;
@@ -205,10 +208,10 @@
#&gt; parent_0 log_k_parent log_k_M1 log_k_M2 f_parent_ilr_1
#&gt; parent_0 1.00000 0.40213 -0.1693 0.02912 -0.4726
#&gt; log_k_parent 0.40213 1.00000 -0.4210 0.07241 -0.5837
-#&gt; log_k_M1 -0.16931 -0.42102 1.0000 -0.37657 0.7438
+#&gt; log_k_M1 -0.16931 -0.42103 1.0000 -0.37657 0.7438
#&gt; log_k_M2 0.02912 0.07241 -0.3766 1.00000 -0.2518
#&gt; f_parent_ilr_1 -0.47263 -0.58367 0.7438 -0.25177 1.0000
-#&gt; f_M1_ilr_1 0.17148 0.42642 -0.8054 0.52648 -0.8602
+#&gt; f_M1_ilr_1 0.17148 0.42643 -0.8054 0.52647 -0.8602
#&gt; f_M1_ilr_1
#&gt; parent_0 0.1715
#&gt; log_k_parent 0.4264
@@ -255,8 +258,8 @@
#&gt; time variable observed predicted residual
#&gt; 0 parent 101.5 1.021e+02 -0.56248
#&gt; 0 parent 101.2 1.021e+02 -0.86248
-#&gt; 1 parent 53.9 4.873e+01 5.17119
-#&gt; 1 parent 47.5 4.873e+01 -1.22881
+#&gt; 1 parent 53.9 4.873e+01 5.17118
+#&gt; 1 parent 47.5 4.873e+01 -1.22882
#&gt; 3 parent 10.4 1.111e+01 -0.70773
#&gt; 3 parent 7.6 1.111e+01 -3.50773
#&gt; 7 parent 1.1 5.772e-01 0.52283
@@ -273,12 +276,12 @@
#&gt; 120 parent 3.5 -2.805e-11 3.50000
#&gt; 0 M1 NA 0.000e+00 NA
#&gt; 0 M1 NA 0.000e+00 NA
-#&gt; 1 M1 36.4 3.479e+01 1.61089
-#&gt; 1 M1 37.4 3.479e+01 2.61089
+#&gt; 1 M1 36.4 3.479e+01 1.61088
+#&gt; 1 M1 37.4 3.479e+01 2.61088
#&gt; 3 M1 34.3 3.937e+01 -5.07027
#&gt; 3 M1 39.8 3.937e+01 0.42973
-#&gt; 7 M1 15.1 1.549e+01 -0.38714
-#&gt; 7 M1 17.8 1.549e+01 2.31286
+#&gt; 7 M1 15.1 1.549e+01 -0.38715
+#&gt; 7 M1 17.8 1.549e+01 2.31285
#&gt; 14 M1 5.8 1.995e+00 3.80469
#&gt; 14 M1 1.2 1.995e+00 -0.79531
#&gt; 28 M1 NA 3.034e-02 NA
@@ -295,16 +298,16 @@
#&gt; 1 M2 4.8 4.455e+00 0.34517
#&gt; 3 M2 20.9 2.153e+01 -0.62527
#&gt; 3 M2 19.3 2.153e+01 -2.22527
-#&gt; 7 M2 42.0 4.192e+01 0.07942
-#&gt; 7 M2 43.1 4.192e+01 1.17942
-#&gt; 14 M2 49.4 4.557e+01 3.83354
-#&gt; 14 M2 44.3 4.557e+01 -1.26646
+#&gt; 7 M2 42.0 4.192e+01 0.07941
+#&gt; 7 M2 43.1 4.192e+01 1.17941
+#&gt; 14 M2 49.4 4.557e+01 3.83353
+#&gt; 14 M2 44.3 4.557e+01 -1.26647
#&gt; 28 M2 34.6 3.547e+01 -0.87275
#&gt; 28 M2 33.0 3.547e+01 -2.47275
#&gt; 60 M2 18.8 1.858e+01 0.21837
#&gt; 60 M2 17.6 1.858e+01 -0.98163
-#&gt; 90 M2 10.6 1.013e+01 0.47131
-#&gt; 90 M2 10.8 1.013e+01 0.67131
+#&gt; 90 M2 10.6 1.013e+01 0.47130
+#&gt; 90 M2 10.8 1.013e+01 0.67130
#&gt; 120 M2 9.8 5.521e+00 4.27893
#&gt; 120 M2 3.3 5.521e+00 -2.22107</div><div class='input'>
</div></pre>

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