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    <h1>Helper functions to create nlme models from mmkin row objects</h1>
    <small class="dont-index">Source: <a href='https://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. They are used internally by the <code><a href='nlme.mmkin.html'>nlme.mmkin()</a></code> method.</p>
    </div>

    <pre class="usage"><span class='fu'>nlme_function</span><span class='op'>(</span><span class='va'>object</span><span class='op'>)</span>

<span class='fu'>mean_degparms</span><span class='op'>(</span><span class='va'>object</span>, random <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>

<span class='fu'>nlme_data</span><span class='op'>(</span><span class='va'>object</span><span class='op'>)</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='va'>sampling_times</span> <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</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='op'>)</span>
<span class='va'>m_SFO</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fu'><a href='mkinmod.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</span>
<span class='va'>d_SFO_1</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>m_SFO</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='fl'>0.1</span><span class='op'>)</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>98</span><span class='op'>)</span>, <span class='va'>sampling_times</span><span class='op'>)</span>
<span class='va'>d_SFO_1_long</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span><span class='op'>(</span><span class='va'>d_SFO_1</span>, time <span class='op'>=</span> <span class='st'>"time"</span><span class='op'>)</span>
<span class='va'>d_SFO_2</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>m_SFO</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='fl'>0.05</span><span class='op'>)</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>102</span><span class='op'>)</span>, <span class='va'>sampling_times</span><span class='op'>)</span>
<span class='va'>d_SFO_2_long</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span><span class='op'>(</span><span class='va'>d_SFO_2</span>, time <span class='op'>=</span> <span class='st'>"time"</span><span class='op'>)</span>
<span class='va'>d_SFO_3</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkinpredict.html'>mkinpredict</a></span><span class='op'>(</span><span class='va'>m_SFO</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>k_parent <span class='op'>=</span> <span class='fl'>0.02</span><span class='op'>)</span>,
  <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>parent <span class='op'>=</span> <span class='fl'>103</span><span class='op'>)</span>, <span class='va'>sampling_times</span><span class='op'>)</span>
<span class='va'>d_SFO_3_long</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span><span class='op'>(</span><span class='va'>d_SFO_3</span>, time <span class='op'>=</span> <span class='st'>"time"</span><span class='op'>)</span>

<span class='va'>d1</span> <span class='op'>&lt;-</span> <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>d_SFO_1</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fl'>3</span>, n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
<span class='va'>d2</span> <span class='op'>&lt;-</span> <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>d_SFO_2</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fl'>2</span>, n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
<span class='va'>d3</span> <span class='op'>&lt;-</span> <span class='fu'><a href='add_err.html'>add_err</a></span><span class='op'>(</span><span class='va'>d_SFO_3</span>, <span class='kw'>function</span><span class='op'>(</span><span class='va'>value</span><span class='op'>)</span> <span class='fl'>4</span>, n <span class='op'>=</span> <span class='fl'>1</span><span class='op'>)</span>
<span class='va'>ds</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span>d1 <span class='op'>=</span> <span class='va'>d1</span>, d2 <span class='op'>=</span> <span class='va'>d2</span>, d3 <span class='op'>=</span> <span class='va'>d3</span><span class='op'>)</span>

<span class='va'>f</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='va'>ds</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='va'>mean_dp</span> <span class='op'>&lt;-</span> <span class='fu'>mean_degparms</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span>
<span class='va'>grouped_data</span> <span class='op'>&lt;-</span> <span class='fu'>nlme_data</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span>
<span class='va'>nlme_f</span> <span class='op'>&lt;-</span> <span class='fu'>nlme_function</span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</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='op'>(</span><span class='st'>"nlme_f"</span>, <span class='va'>nlme_f</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/assign.html'>assign</a></span><span class='op'>(</span><span class='st'>"grouped_data"</span>, <span class='va'>grouped_data</span>, <span class='fu'><a href='https://rdrr.io/r/base/environment.html'>globalenv</a></span><span class='op'>(</span><span class='op'>)</span><span class='op'>)</span>

<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'><a href='https://svn.r-project.org/R-packages/trunk/nlme/'>nlme</a></span><span class='op'>)</span>
<span class='va'>m_nlme</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>value</span> <span class='op'>~</span> <span class='fu'>nlme_f</span><span class='op'>(</span><span class='va'>name</span>, <span class='va'>time</span>, <span class='va'>parent_0</span>, <span class='va'>log_k_parent_sink</span><span class='op'>)</span>,
  data <span class='op'>=</span> <span class='va'>grouped_data</span>,
  fixed <span class='op'>=</span> <span class='va'>parent_0</span> <span class='op'>+</span> <span class='va'>log_k_parent_sink</span> <span class='op'>~</span> <span class='fl'>1</span>,
  random <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/pdDiag.html'>pdDiag</a></span><span class='op'>(</span><span class='va'>parent_0</span> <span class='op'>+</span> <span class='va'>log_k_parent_sink</span> <span class='op'>~</span> <span class='fl'>1</span><span class='op'>)</span>,
  start <span class='op'>=</span> <span class='va'>mean_dp</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/summary.html'>summary</a></span><span class='op'>(</span><span class='va'>m_nlme</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Nonlinear mixed-effects model fit by maximum likelihood
#&gt;   Model: value ~ nlme_f(name, time, parent_0, log_k_parent_sink) 
#&gt;  Data: grouped_data 
#&gt;        AIC      BIC    logLik
#&gt;   252.7798 262.1358 -121.3899
#&gt; 
#&gt; Random effects:
#&gt;  Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
#&gt;  Level: ds
#&gt;  Structure: Diagonal
#&gt;             parent_0 log_k_parent_sink Residual
#&gt; StdDev: 0.0006768135         0.6800777 2.489397
#&gt; 
#&gt; Fixed effects: parent_0 + log_k_parent_sink ~ 1 
#&gt;                       Value Std.Error DF   t-value p-value
#&gt; parent_0          101.74884 0.6456014 44 157.60321       0
#&gt; log_k_parent_sink  -3.05575 0.4015811 44  -7.60929       0
#&gt;  Correlation: 
#&gt;                   prnt_0
#&gt; log_k_parent_sink 0.026 
#&gt; 
#&gt; Standardized Within-Group Residuals:
#&gt;        Min         Q1        Med         Q3        Max 
#&gt; -2.1317488 -0.6878121  0.0828385  0.8592270  2.9529864 
#&gt; 
#&gt; Number of Observations: 48
#&gt; Number of Groups: 3 </div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/pkg/nlme/man/augPred.html'>augPred</a></span><span class='op'>(</span><span class='va'>m_nlme</span>, level <span class='op'>=</span> <span class='fl'>0</span><span class='op'>:</span><span class='fl'>1</span><span class='op'>)</span>, layout <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fl'>1</span><span class='op'>)</span><span class='op'>)</span>
</div><div class='img'><img src='nlme-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='co'># augPred does not work on fits with more than one state</span>
<span class='co'># variable</span>
<span class='co'>#</span>
<span class='co'># The procedure is greatly simplified by the nlme.mmkin function</span>
<span class='va'>f_nlme</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span><span class='op'>(</span><span class='va'>f</span><span class='op'>)</span>
</div><div class='output co'>#&gt; <span class='warning'>Warning: Iteration 1, LME step: nlminb() did not converge (code = 1). Do increase 'msMaxIter'!</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/r/graphics/plot.default.html'>plot</a></span><span class='op'>(</span><span class='va'>f_nlme</span><span class='op'>)</span>
</div><div class='img'><img src='nlme-2.png' alt='' width='700' height='433' /></div></pre>
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