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diff --git a/docs/reference/logLik.mkinfit.html b/docs/reference/logLik.mkinfit.html
index 33d9eb36..303a337d 100644
--- a/docs/reference/logLik.mkinfit.html
+++ b/docs/reference/logLik.mkinfit.html
@@ -1,6 +1,6 @@
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@@ -9,17 +9,17 @@
<title>Calculated the log-likelihood of a fitted mkinfit object — logLik.mkinfit • mkin</title>
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@@ -55,7 +55,8 @@ In the case of iterative reweighting, the variances obtained by this
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@@ -71,14 +72,15 @@ In the case of iterative reweighting, the variances obtained by this
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@@ -141,12 +143,12 @@ In the case of iterative reweighting, the variances obtained by this
<div class="ref-description">
<p>This function simply calculates the product of the likelihood densities
- calculated using <code>dnorm</code>, i.e. assuming normal distribution.</p>
+ calculated using <code><a href='https://www.rdocumentation.org/packages/stats/topics/Normal'>dnorm</a></code>, i.e. assuming normal distribution.</p>
<p>The total number of estimated parameters returned with the value
of the likelihood is calculated as the sum of fitted degradation
model parameters and the fitted error model parameters.</p>
<p>For the case of unweighted least squares fitting, we calculate one
- constant standard deviation from the residuals using <code>sd</code>
+ constant standard deviation from the residuals using <code><a href='https://www.rdocumentation.org/packages/stats/topics/sd'>sd</a></code>
and add one to the number of fitted degradation model parameters.</p>
<p>For the case of manual weighting, we use the weight given for each
observation as standard deviation in calculating its likelihood
@@ -162,7 +164,7 @@ In the case of iterative reweighting, the variances obtained by this
</div>
<pre class="usage"><span class='co'># S3 method for mkinfit</span>
-<span class='fu'>logLik</span>(<span class='no'>object</span>, <span class='no'>...</span>)</pre>
+<span class='fu'><a href='https://www.rdocumentation.org/packages/stats/topics/logLik'>logLik</a></span>(<span class='no'>object</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
@@ -179,7 +181,7 @@ In the case of iterative reweighting, the variances obtained by this
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
- <p>An object of class <code>logLik</code> with the number of
+ <p>An object of class <code><a href='https://www.rdocumentation.org/packages/stats/topics/logLik'>logLik</a></code> with the number of
estimated parameters (degradation model parameters plus variance
model parameters) as attribute.</p>
@@ -193,18 +195,10 @@ In the case of iterative reweighting, the variances obtained by this
<pre class="examples"><div class='input'> <span class='no'>sfo_sfo</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='mkinsub.html'>mkinsub</a></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='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</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'>d_t</span> <span class='kw'>&lt;-</span> <span class='no'>FOCUS_2006_D</span>
- <span class='no'>d_t</span>[<span class='fl'>23</span>:<span class='fl'>24</span>, <span class='st'>"value"</span>] <span class='kw'>&lt;-</span> <span class='fu'>c</span>(<span class='fl'>NA</span>, <span class='fl'>NA</span>) <span class='co'># can't cope with zero values at the moment</span>
- <span class='no'>f_nw</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># no weighting (weights are unity)</span>
- <span class='no'>f_obs</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>reweight.method</span> <span class='kw'>=</span> <span class='st'>"obs"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
- <span class='no'>f_tc</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>reweight.method</span> <span class='kw'>=</span> <span class='st'>"tc"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
- <span class='no'>d_t</span>$<span class='no'>err</span> <span class='kw'>&lt;-</span> <span class='no'>d_t</span>$<span class='no'>value</span> <span class='co'># Manual weighting assuming sigma ~ y</span>
- <span class='no'>f_man</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>err</span> <span class='kw'>=</span> <span class='st'>"err"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
- <span class='fu'>AIC</span>(<span class='no'>f_nw</span>, <span class='no'>f_obs</span>, <span class='no'>f_tc</span>, <span class='no'>f_man</span>)</div><div class='output co'>#&gt; df AIC
-#&gt; f_nw 5 204.4619
-#&gt; f_obs 6 205.8727
-#&gt; f_tc 6 143.8773
-#&gt; f_man 4 291.8000</div></pre>
+ )</div><div class='output co'>#&gt; <span class='error'>Error in mkinmod(parent = mkinsub("SFO", to = "m1"), m1 = mkinsub("SFO")): konnte Funktion "mkinmod" nicht finden</span></div><div class='input'> <span class='no'>d_t</span> <span class='kw'>&lt;-</span> <span class='no'>FOCUS_2006_D</span>
+ <span class='no'>d_t</span>[<span class='fl'>23</span>:<span class='fl'>24</span>, <span class='st'>"value"</span>] <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>NA</span>, <span class='fl'>NA</span>) <span class='co'># can't cope with zero values at the moment</span>
+ <span class='no'>f_nw</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># no weighting (weights are unity)</span></div><div class='output co'>#&gt; <span class='error'>Error in mkinfit(sfo_sfo, d_t, quiet = TRUE): konnte Funktion "mkinfit" nicht finden</span></div><div class='input'> <span class='no'>f_obs</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>reweight.method</span> <span class='kw'>=</span> <span class='st'>"obs"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='error'>Error in mkinfit(sfo_sfo, d_t, reweight.method = "obs", quiet = TRUE): konnte Funktion "mkinfit" nicht finden</span></div><div class='input'> <span class='no'>f_tc</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>reweight.method</span> <span class='kw'>=</span> <span class='st'>"tc"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='error'>Error in mkinfit(sfo_sfo, d_t, reweight.method = "tc", quiet = TRUE): konnte Funktion "mkinfit" nicht finden</span></div><div class='input'> <span class='no'>d_t</span>$<span class='no'>err</span> <span class='kw'>&lt;-</span> <span class='no'>d_t</span>$<span class='no'>value</span> <span class='co'># Manual weighting assuming sigma ~ y</span>
+ <span class='no'>f_man</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>sfo_sfo</span>, <span class='no'>d_t</span>, <span class='kw'>err</span> <span class='kw'>=</span> <span class='st'>"err"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; <span class='error'>Error in mkinfit(sfo_sfo, d_t, err = "err", quiet = TRUE): konnte Funktion "mkinfit" nicht finden</span></div><div class='input'> <span class='fu'><a href='https://www.rdocumentation.org/packages/stats/topics/AIC'>AIC</a></span>(<span class='no'>f_nw</span>, <span class='no'>f_obs</span>, <span class='no'>f_tc</span>, <span class='no'>f_man</span>)</div><div class='output co'>#&gt; <span class='error'>Error in AIC(f_nw, f_obs, f_tc, f_man): Objekt 'f_nw' nicht gefunden</span></div></pre>
</div>
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<h2>Contents</h2>
@@ -219,9 +213,7 @@ In the case of iterative reweighting, the variances obtained by this
</ul>
<h2>Author</h2>
-
- Johannes Ranke
-
+ <p>Johannes Ranke</p>
</div>
</div>
@@ -231,9 +223,8 @@ In the case of iterative reweighting, the variances obtained by this
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