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<h1>Helper functions to create nlme models from mmkin row objects</h1>
<small class="dont-index">Source: <a href='http://github.com/jranke/mkin/blob/master/R/nlme.R'><code>R/nlme.R</code></a></small>
<div class="hidden name"><code>nlme.Rd</code></div>
</div>
<div class="ref-description">
<p>These functions facilitate setting up a nonlinear mixed effects model for
an mmkin row object. An mmkin row object is essentially a list of mkinfit
objects that have been obtained by fitting the same model to a list of
datasets.</p>
</div>
<pre class="usage"><span class='fu'>nlme_function</span>(<span class='no'>object</span>)
<span class='fu'>mean_degparms</span>(<span class='no'>object</span>, <span class='kw'>random</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>nlme_data</span>(<span class='no'>object</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>
<tr>
<th>object</th>
<td><p>An mmkin row object containing several fits of the same model to different datasets</p></td>
</tr>
<tr>
<th>random</th>
<td><p>Should a list with fixed and random effects be returned?</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A function that can be used with nlme</p>
<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>
<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>
<div class='dont-index'><p><code><a href='nlme.mmkin.html'>nlme.mmkin</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='no'>sampling_times</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>3</span>, <span class='fl'>7</span>, <span class='fl'>14</span>, <span class='fl'>28</span>, <span class='fl'>60</span>, <span class='fl'>90</span>, <span class='fl'>120</span>)
<span class='no'>m_SFO</span> <span class='kw'><-</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='no'>d_SFO_1</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_SFO</span>,
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.1</span>),
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>98</span>), <span class='no'>sampling_times</span>)
<span class='no'>d_SFO_1_long</span> <span class='kw'><-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span>(<span class='no'>d_SFO_1</span>, <span class='kw'>time</span> <span class='kw'>=</span> <span class='st'>"time"</span>)
<span class='no'>d_SFO_2</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_SFO</span>,
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.05</span>),
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>102</span>), <span class='no'>sampling_times</span>)
<span class='no'>d_SFO_2_long</span> <span class='kw'><-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span>(<span class='no'>d_SFO_2</span>, <span class='kw'>time</span> <span class='kw'>=</span> <span class='st'>"time"</span>)
<span class='no'>d_SFO_3</span> <span class='kw'><-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span>(<span class='no'>m_SFO</span>,
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>k_parent</span> <span class='kw'>=</span> <span class='fl'>0.02</span>),
<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fl'>103</span>), <span class='no'>sampling_times</span>)
<span class='no'>d_SFO_3_long</span> <span class='kw'><-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span>(<span class='no'>d_SFO_3</span>, <span class='kw'>time</span> <span class='kw'>=</span> <span class='st'>"time"</span>)
<span class='no'>d1</span> <span class='kw'><-</span> <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_SFO_1</span>, <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fl'>3</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>1</span>)
<span class='no'>d2</span> <span class='kw'><-</span> <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_SFO_2</span>, <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fl'>2</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>1</span>)
<span class='no'>d3</span> <span class='kw'><-</span> <span class='fu'><a href='add_err.html'>add_err</a></span>(<span class='no'>d_SFO_3</span>, <span class='kw'>function</span>(<span class='no'>value</span>) <span class='fl'>4</span>, <span class='kw'>n</span> <span class='kw'>=</span> <span class='fl'>1</span>)
<span class='no'>ds</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>d1</span> <span class='kw'>=</span> <span class='no'>d1</span>, <span class='kw'>d2</span> <span class='kw'>=</span> <span class='no'>d2</span>, <span class='kw'>d3</span> <span class='kw'>=</span> <span class='no'>d3</span>)
<span class='no'>f</span> <span class='kw'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='st'>"SFO"</span>, <span class='no'>ds</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>mean_dp</span> <span class='kw'><-</span> <span class='fu'>mean_degparms</span>(<span class='no'>f</span>)
<span class='no'>grouped_data</span> <span class='kw'><-</span> <span class='fu'>nlme_data</span>(<span class='no'>f</span>)
<span class='no'>nlme_f</span> <span class='kw'><-</span> <span class='fu'>nlme_function</span>(<span class='no'>f</span>)
<span class='co'># These assignments are necessary for these objects to be</span>
<span class='co'># visible to nlme and augPred when evaluation is done by</span>
<span class='co'># pkgdown to generated the html docs.</span>
<span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span>(<span class='st'>"nlme_f"</span>, <span class='no'>nlme_f</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span>())
<span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span>(<span class='st'>"grouped_data"</span>, <span class='no'>grouped_data</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span>())
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>nlme</span>)
<span class='no'>m_nlme</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>value</span> ~ <span class='fu'>nlme_f</span>(<span class='no'>name</span>, <span class='no'>time</span>, <span class='no'>parent_0</span>, <span class='no'>log_k_parent_sink</span>),
<span class='kw'>data</span> <span class='kw'>=</span> <span class='no'>grouped_data</span>,
<span class='kw'>fixed</span> <span class='kw'>=</span> <span class='no'>parent_0</span> + <span class='no'>log_k_parent_sink</span> ~ <span class='fl'>1</span>,
<span class='kw'>random</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/pdDiag.html'>pdDiag</a></span>(<span class='no'>parent_0</span> + <span class='no'>log_k_parent_sink</span> ~ <span class='fl'>1</span>),
<span class='kw'>start</span> <span class='kw'>=</span> <span class='no'>mean_dp</span>)
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span>(<span class='no'>m_nlme</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood
#> Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink)
#> Data: grouped_data
#> AIC BIC logLik
#> 252.7798 262.1358 -121.3899
#>
#> Random effects:
#> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
#> Level: ds
#> Structure: Diagonal
#> parent_0 log_k_parent_sink Residual
#> StdDev: 0.004139378 0.6800778 2.489396
#>
#> Fixed effects: parent_0 + log_k_parent_sink ~ 1
#> Value Std.Error DF t-value p-value
#> parent_0 101.74884 0.6456057 44 157.60213 0
#> log_k_parent_sink -3.05575 0.4015812 44 -7.60929 0
#> Correlation:
#> prnt_0
#> log_k_parent_sink 0.026
#>
#> Standardized Within-Group Residuals:
#> Min Q1 Med Q3 Max
#> -2.13168782 -0.68780415 0.08282907 0.85913228 2.95298904
#>
#> Number of Observations: 48
#> Number of Groups: 3 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/base/plot.html'>plot</a></span>(<span class='fu'><a href='https://rdrr.io/pkg/nlme/man/augPred.html'>augPred</a></span>(<span class='no'>m_nlme</span>, <span class='kw'>level</span> <span class='kw'>=</span> <span class='fl'>0</span>:<span class='fl'>1</span>), <span class='kw'>layout</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='fl'>3</span>, <span class='fl'>1</span>))</div><div class='img'><img src='nlme-1.png' alt='' width='700' height='433' /></div><div class='input'># augPred does not seem to work on fits with more than one state
# variable
</div></pre>
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