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authorJohannes Ranke <jranke@uni-bremen.de>2020-05-26 18:38:51 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2020-05-26 18:52:01 +0200
commit675a733fa2acc08daabb9b8b571c7d658f281f73 (patch)
treeef29cec38aa6d446f7956c0e423cca6bed2e21c0 /docs/reference/nlme.html
parent5e85d8856e7c9db3c52bb6ac5a0a81e2f0c6181c (diff)
Use all cores per default, confint tolerance
Also, use more intelligent starting values for the variance of the random effects for saemix. While this does not appear to speed up the convergence, it shows where this variance is greatly reduced by using mixed-effects models as opposed to the separate independent fits.
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diff --git a/docs/reference/nlme.html b/docs/reference/nlme.html
index b2d415dc..3462e52e 100644
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@@ -75,7 +75,7 @@ datasets. They are used internally by the nlme.mmkin() method." />
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">mkin</a>
- <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.9.50.2</span>
+ <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">0.9.50.3</span>
</span>
</div>
@@ -178,7 +178,7 @@ datasets. They are used internally by the <code><a href='nlme.mmkin.html'>nlme.m
<p>If random is FALSE (default), a named vector containing mean values
of the fitted degradation model parameters. If random is TRUE, a list with
fixed and random effects, in the format required by the start argument of
-nlme for the case of a single grouping variable ds?</p>
+nlme for the case of a single grouping variable ds.</p>
<p>A <code><a href='https://rdrr.io/pkg/nlme/man/groupedData.html'>groupedData</a></code> object</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>

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