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-rw-r--r--docs/reference/sigma_twocomp.html22
-rw-r--r--docs/reference/synthetic_data_for_UBA_2014.html8
2 files changed, 14 insertions, 16 deletions
diff --git a/docs/reference/sigma_twocomp.html b/docs/reference/sigma_twocomp.html
index ee956f9f..ef62212a 100644
--- a/docs/reference/sigma_twocomp.html
+++ b/docs/reference/sigma_twocomp.html
@@ -8,11 +8,13 @@
<title>Two component error model — sigma_twocomp • mkin</title>
+
<!-- jquery -->
<script src="https://cdnjs.cloudflare.com/ajax/libs/jquery/3.3.1/jquery.min.js" integrity="sha256-FgpCb/KJQlLNfOu91ta32o/NMZxltwRo8QtmkMRdAu8=" crossorigin="anonymous"></script>
<!-- Bootstrap -->
<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/css/bootstrap.min.css" integrity="sha256-916EbMg70RQy9LHiGkXzG8hSg9EdNy97GazNG/aiY1w=" crossorigin="anonymous" />
+
<script src="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha256-U5ZEeKfGNOja007MMD3YBI0A3OSZOQbeG6z2f2Y0hu8=" crossorigin="anonymous"></script>
<!-- Font Awesome icons -->
@@ -32,11 +34,12 @@
-<meta property="og:title" content="Two component error model — sigma_twocomp" />
+<meta property="og:title" content="Two component error model — sigma_twocomp" />
<meta property="og:description" content="Function describing the standard deviation of the measurement error
in dependence of the measured value \(y\):
$$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$
+ sigma = sqrt(sigma_low^2 + y^2 * rsd_high^2)
This is the error model used for example by Werner et al. (1978). The model
proposed by Rocke and Lorenzato (1995) can be written in this form as well,
but assumes approximate lognormal distribution of errors for high values of y." />
@@ -44,6 +47,7 @@ This is the error model used for example by Werner et al. (1978). The model
+
<!-- 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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@@ -114,7 +118,6 @@ This is the error model used for example by Werner et al. (1978). The model
<a href="../news/index.html">News</a>
</li>
</ul>
-
<ul class="nav navbar-nav navbar-right">
</ul>
@@ -136,18 +139,17 @@ This is the error model used for example by Werner et al. (1978). The model
</div>
<div class="ref-description">
-
<p>Function describing the standard deviation of the measurement error
in dependence of the measured value \(y\):</p>
-<p>$$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$</p>
+<p>$$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$
+ sigma = sqrt(sigma_low^2 + y^2 * rsd_high^2)</p>
<p>This is the error model used for example by Werner et al. (1978). The model
proposed by Rocke and Lorenzato (1995) can be written in this form as well,
but assumes approximate lognormal distribution of errors for high values of y.</p>
-
</div>
<pre class="usage"><span class='fu'>sigma_twocomp</span>(<span class='no'>y</span>, <span class='no'>sigma_low</span>, <span class='no'>rsd_high</span>)</pre>
-
+
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
@@ -165,11 +167,10 @@ This is the error model used for example by Werner et al. (1978). The model
the magnitude of the observed value</p></td>
</tr>
</table>
-
+
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>The standard deviation of the response variable.</p>
-
<h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
<p>Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
@@ -177,18 +178,15 @@ This is the error model used for example by Werner et al. (1978). The model
24(11), 1895-1898.</p>
<p>Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for
measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p>
-
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
-
<li><a href="#value">Value</a></li>
-
<li><a href="#references">References</a></li>
- </ul>
+ </ul>
</div>
</div>
diff --git a/docs/reference/synthetic_data_for_UBA_2014.html b/docs/reference/synthetic_data_for_UBA_2014.html
index f23b77b0..eb5b8c65 100644
--- a/docs/reference/synthetic_data_for_UBA_2014.html
+++ b/docs/reference/synthetic_data_for_UBA_2014.html
@@ -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 </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_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>
@@ -282,8 +282,8 @@ Compare also the code in the example section to see the degradation models." />
<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 22:46:31 2019
-#&gt; Date of summary: Mon Oct 21 22:46:31 2019
+#&gt; Date of fit: Mon Oct 21 22:49:25 2019
+#&gt; Date of summary: Mon Oct 21 22:49:25 2019
#&gt;
#&gt; Equations:
#&gt; d_parent/dt = - k_parent * parent
@@ -292,7 +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 2.45 s
+#&gt; Fitted using 847 model solutions performed in 2.43 s
#&gt;
#&gt; Error model: Constant variance
#&gt;

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