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authorJohannes Ranke <jranke@uni-bremen.de>2015-06-23 15:19:21 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2015-06-23 15:19:21 +0200
commit005a39e3f4413ae27d8334b8000abd1d25108a7a (patch)
treed7803cdd374f9cfcf4c3a7618f46c93b9072a280 /vignettes/FOCUS_D.html
parente2c33e96775d27edc40be4bcedc6077135e90b0a (diff)
Vignettes rebuilt by staticdocs::build_site() for static documentation on r-forgev0.9-38
Diffstat (limited to 'vignettes/FOCUS_D.html')
-rw-r--r--vignettes/FOCUS_D.html8
1 files changed, 4 insertions, 4 deletions
diff --git a/vignettes/FOCUS_D.html b/vignettes/FOCUS_D.html
index 0ec2542c..01d5d4f3 100644
--- a/vignettes/FOCUS_D.html
+++ b/vignettes/FOCUS_D.html
@@ -135,10 +135,10 @@ print(FOCUS_2006_D)</code></pre>
<p><img 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" title alt width="672" /></p>
<p>A comprehensive report of the results is obtained using the <code>summary</code> method for <code>mkinfit</code> objects.</p>
<pre class="r"><code>summary(fit)</code></pre>
-<pre><code>## mkin version: 0.9.37
+<pre><code>## mkin version: 0.9.38
## R version: 3.2.1
-## Date of fit: Tue Jun 23 13:14:52 2015
-## Date of summary: Tue Jun 23 13:14:52 2015
+## Date of fit: Tue Jun 23 15:18:13 2015
+## Date of summary: Tue Jun 23 15:18:14 2015
##
## Equations:
## d_parent = - k_parent_sink * parent - k_parent_m1 * parent
@@ -146,7 +146,7 @@ print(FOCUS_2006_D)</code></pre>
##
## Model predictions using solution type deSolve
##
-## Fitted with method Port using 153 model solutions performed in 0.682 s
+## Fitted with method Port using 153 model solutions performed in 0.749 s
##
## Weighting: none
##

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