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    <h1>Fit nonlinear mixed models with SAEM</h1>
    <small class="dont-index">Source: <a href='https://github.com/jranke/mkin/blob/master/R/saem.R'><code>R/saem.R</code></a></small>
    <div class="hidden name"><code>saem.Rd</code></div>
    </div>

    <div class="ref-description">
    <p>This function uses <code><a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix::saemix()</a></code> as a backend for fitting nonlinear mixed
effects models created from <a href='mmkin.html'>mmkin</a> row objects using the Stochastic Approximation
Expectation Maximisation algorithm (SAEM).</p>
    </div>

    <pre class="usage"><span class='fu'>saem</span><span class='op'>(</span><span class='va'>object</span>, <span class='va'>control</span>, <span class='va'>...</span><span class='op'>)</span>

<span class='co'># S3 method for mmkin</span>
<span class='fu'>saem</span><span class='op'>(</span>
  <span class='va'>object</span>,
  control <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>displayProgress <span class='op'>=</span> <span class='cn'>FALSE</span>, print <span class='op'>=</span> <span class='cn'>FALSE</span>, save <span class='op'>=</span> <span class='cn'>FALSE</span>, save.graphs <span class='op'>=</span>
    <span class='cn'>FALSE</span><span class='op'>)</span>,
  cores <span class='op'>=</span> <span class='fl'>1</span>,
  verbose <span class='op'>=</span> <span class='cn'>FALSE</span>,
  suppressPlot <span class='op'>=</span> <span class='cn'>TRUE</span>,
  quiet <span class='op'>=</span> <span class='cn'>FALSE</span>,
  <span class='va'>...</span>
<span class='op'>)</span>

<span class='co'># S3 method for saem.mmkin</span>
<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>x</span>, digits <span class='op'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/Extremes.html'>max</a></span><span class='op'>(</span><span class='fl'>3</span>, <span class='fu'><a href='https://rdrr.io/r/base/options.html'>getOption</a></span><span class='op'>(</span><span class='st'>"digits"</span><span class='op'>)</span> <span class='op'>-</span> <span class='fl'>3</span><span class='op'>)</span>, <span class='va'>...</span><span class='op'>)</span>

<span class='fu'>saemix_model</span><span class='op'>(</span><span class='va'>object</span>, cores <span class='op'>=</span> <span class='fl'>1</span>, verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</span><span class='op'>)</span>

<span class='fu'>saemix_data</span><span class='op'>(</span><span class='va'>object</span>, verbose <span class='op'>=</span> <span class='cn'>FALSE</span>, <span class='va'>...</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 <a href='mmkin.html'>mmkin</a> row object containing several fits of the same
<a href='mkinmod.html'>mkinmod</a> model to different datasets</p></td>
    </tr>
    <tr>
      <th>control</th>
      <td><p>Passed to <a href='https://rdrr.io/pkg/saemix/man/saemix.html'>saemix::saemix</a></p></td>
    </tr>
    <tr>
      <th>...</th>
      <td><p>Further parameters passed to <a href='https://rdrr.io/pkg/saemix/man/saemixModel.html'>saemix::saemixModel</a>.</p></td>
    </tr>
    <tr>
      <th>cores</th>
      <td><p>The number of cores to be used for multicore processing using
<code><a href='https://rdrr.io/r/parallel/mclapply.html'>parallel::mclapply()</a></code>. Using more than 1 core is experimental and may
lead to excessive forking, apparently depending on the BLAS version
used.</p></td>
    </tr>
    <tr>
      <th>verbose</th>
      <td><p>Should we print information about created objects of
type <a href='https://rdrr.io/pkg/saemix/man/SaemixModel-class.html'>saemix::SaemixModel</a> and <a href='https://rdrr.io/pkg/saemix/man/SaemixData-class.html'>saemix::SaemixData</a>?</p></td>
    </tr>
    <tr>
      <th>suppressPlot</th>
      <td><p>Should we suppress any plotting that is done
by the saemix function?</p></td>
    </tr>
    <tr>
      <th>quiet</th>
      <td><p>Should we suppress the messages saemix prints at the beginning
and the end of the optimisation process?</p></td>
    </tr>
    <tr>
      <th>x</th>
      <td><p>An saem.mmkin object to print</p></td>
    </tr>
    <tr>
      <th>digits</th>
      <td><p>Number of digits to use for printing</p></td>
    </tr>
    </table>

    <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>

    <p>An S3 object of class 'saem.mmkin', containing the fitted
<a href='https://rdrr.io/pkg/saemix/man/SaemixObject-class.html'>saemix::SaemixObject</a> as a list component named 'so'. The
object also inherits from 'mixed.mmkin'.</p>
<p>An <a href='https://rdrr.io/pkg/saemix/man/SaemixModel-class.html'>saemix::SaemixModel</a> object.</p>
<p>An <a href='https://rdrr.io/pkg/saemix/man/SaemixData-class.html'>saemix::SaemixData</a> object.</p>
    <h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>

    <p>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 using <a href='mkinfit.html'>mkinfit</a>.</p>
<p>Starting values for the fixed effects (population mean parameters, argument
psi0 of <code><a href='https://rdrr.io/pkg/saemix/man/saemixModel.html'>saemix::saemixModel()</a></code> are the mean values of the parameters found
using <a href='mmkin.html'>mmkin</a>.</p>
    <h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>

    <div class='dont-index'><p><a href='summary.saem.mmkin.html'>summary.saem.mmkin</a> <a href='plot.mixed.mmkin.html'>plot.mixed.mmkin</a></p></div>

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='co'># \dontrun{</span>
<span class='va'>ds</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span><span class='op'>(</span><span class='va'>experimental_data_for_UBA_2019</span><span class='op'>[</span><span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>]</span>,
 <span class='kw'>function</span><span class='op'>(</span><span class='va'>x</span><span class='op'>)</span> <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span><span class='op'>(</span><span class='va'>x</span><span class='op'>$</span><span class='va'>data</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='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span><span class='op'>)</span><span class='op'>]</span><span class='op'>)</span><span class='op'>)</span>
<span class='fu'><a href='https://rdrr.io/r/base/names.html'>names</a></span><span class='op'>(</span><span class='va'>ds</span><span class='op'>)</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/base/paste.html'>paste</a></span><span class='op'>(</span><span class='st'>"Dataset"</span>, <span class='fl'>6</span><span class='op'>:</span><span class='fl'>10</span><span class='op'>)</span>
<span class='va'>f_mmkin_parent_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='va'>ds</span>, cores <span class='op'>=</span> <span class='fl'>1</span>,
  state.ini <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'>100</span><span class='op'>)</span>, fixed_initials <span class='op'>=</span> <span class='st'>"parent"</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='va'>f_saem_p0_fixed</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent_p0_fixed</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:47:58 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:00 2020"</div><div class='input'>
<span class='va'>f_mmkin_parent</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></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='st'>"SFO"</span>, <span class='st'>"FOMC"</span>, <span class='st'>"DFOP"</span><span class='op'>)</span>, <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='va'>f_saem_sfo</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:01 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:03 2020"</div><div class='input'><span class='va'>f_saem_fomc</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:03 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:05 2020"</div><div class='input'><span class='va'>f_saem_dfop</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent</span><span class='op'>[</span><span class='st'>"DFOP"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:06 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:08 2020"</div><div class='input'>
<span class='co'># The returned saem.mmkin object contains an SaemixObject, therefore we can use</span>
<span class='co'># functions from saemix</span>
<span class='kw'><a href='https://rdrr.io/r/base/library.html'>library</a></span><span class='op'>(</span><span class='va'>saemix</span><span class='op'>)</span>
</div><div class='output co'>#&gt; <span class='message'>Package saemix, version 3.1.9000</span>
#&gt; <span class='message'>  please direct bugs, questions and feedback to emmanuelle.comets@inserm.fr</span></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>f_saem_sfo</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_dfop</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt;        AIC      BIC
#&gt; 1 624.2484 622.2956
#&gt; 2 467.7096 464.9757
#&gt; 3 495.4373 491.9222</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"convergence"</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Plotting convergence plots</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"individual.fit"</span><span class='op'>)</span>
</div><div class='img'><img src='saem-1.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Plotting individual fits</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"npde"</span><span class='op'>)</span>
</div><div class='img'><img src='saem-2.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; Simulating data using nsim = 1000 simulated datasets
#&gt; Computing WRES and npde .
#&gt; Plotting npde</div><div class='img'><img src='saem-3.png' alt='' width='700' height='433' /></div><div class='output co'>#&gt; ---------------------------------------------
#&gt; Distribution of npde:
#&gt;            mean= -0.01528   (SE= 0.098 )
#&gt;        variance= 0.862   (SE= 0.13 )
#&gt;        skewness= 0.5016 
#&gt;        kurtosis= 1.18 
#&gt; ---------------------------------------------
#&gt; 
#&gt; Statistical tests
#&gt;   Wilcoxon signed rank test  : 0.679
#&gt;   Fisher variance test       : 0.36
#&gt;   SW test of normality       : 0.0855 .
#&gt; Global adjusted p-value      : 0.257
#&gt; ---
#&gt; Signif. codes: '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 
#&gt; ---------------------------------------------</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, plot.type <span class='op'>=</span> <span class='st'>"vpc"</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Performing simulations under the model.
#&gt; Plotting VPC
#&gt; Method used for VPC: binning by quantiles on X , dividing into the following intervals
#&gt;   Interval  Centered.On
#&gt; 1 (-1,3]      1.3      
#&gt; 2 (3,8]       7.4      
#&gt; 3 (8,14]     13.2      
#&gt; 4 (14,21]    20.5      
#&gt; 5 (21,37.7]  29.5      
#&gt; 6 (37.7,60]  50.4      
#&gt; 7 (60,90]    76.6      
#&gt; 8 (90,120]  109.0      
#&gt; 9 (120,180] 156.0      </div><div class='img'><img src='saem-4.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='va'>f_mmkin_parent_tc</span> <span class='op'>&lt;-</span> <span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span><span class='op'>(</span><span class='va'>f_mmkin_parent</span>, error_model <span class='op'>=</span> <span class='st'>"tc"</span><span class='op'>)</span>
<span class='va'>f_saem_fomc_tc</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin_parent_tc</span><span class='op'>[</span><span class='st'>"FOMC"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:11 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:16 2020"</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/compare.saemix.html'>compare.saemix</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span><span class='va'>f_saem_fomc</span><span class='op'>$</span><span class='va'>so</span>, <span class='va'>f_saem_fomc_tc</span><span class='op'>$</span><span class='va'>so</span><span class='op'>)</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Likelihoods computed by importance sampling </div><div class='output co'>#&gt;        AIC      BIC
#&gt; 1 467.7096 464.9757
#&gt; 2 469.5208 466.3963</div><div class='input'>
<span class='va'>sfo_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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
  A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</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='va'>fomc_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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"FOMC"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
  A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</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='va'>dfop_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='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"DFOP"</span>, <span class='st'>"A1"</span><span class='op'>)</span>,
  A1 <span class='op'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span><span class='op'>(</span><span class='st'>"SFO"</span><span class='op'>)</span><span class='op'>)</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='co'># The following fit uses analytical solutions for SFO-SFO and DFOP-SFO,</span>
<span class='co'># and compiled ODEs for FOMC, both are fast</span>
<span class='va'>f_mmkin</span> <span class='op'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span><span class='op'>(</span><span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span><span class='op'>(</span>
    <span class='st'>"SFO-SFO"</span> <span class='op'>=</span> <span class='va'>sfo_sfo</span>, <span class='st'>"FOMC-SFO"</span> <span class='op'>=</span> <span class='va'>fomc_sfo</span>, <span class='st'>"DFOP-SFO"</span> <span class='op'>=</span> <span class='va'>dfop_sfo</span><span class='op'>)</span>,
  <span class='va'>ds</span>, quiet <span class='op'>=</span> <span class='cn'>TRUE</span><span class='op'>)</span>
<span class='co'># These take about five seconds each on this system, as we use</span>
<span class='co'># analytical solutions written for saemix. When using the analytical</span>
<span class='co'># solutions written for mkin this took around four minutes</span>
<span class='va'>f_saem_sfo_sfo</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>[</span><span class='st'>"SFO-SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:18 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:23 2020"</div><div class='input'><span class='va'>f_saem_dfop_sfo</span> <span class='op'>&lt;-</span> <span class='fu'>saem</span><span class='op'>(</span><span class='va'>f_mmkin</span><span class='op'>[</span><span class='st'>"DFOP-SFO"</span>, <span class='op'>]</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Running main SAEM algorithm
#&gt; [1] "Wed Nov 11 19:48:23 2020"
#&gt; ....
#&gt;     Minimisation finished
#&gt; [1] "Wed Nov 11 19:48:32 2020"</div><div class='input'><span class='co'># We can use print, plot and summary methods to check the results</span>
<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span><span class='op'>)</span>
</div><div class='output co'>#&gt; Kinetic nonlinear mixed-effects model fit by SAEM
#&gt; Structural model:
#&gt; d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
#&gt;            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
#&gt;            * parent
#&gt; d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
#&gt;            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
#&gt;            exp(-k2 * time))) * parent - k_A1 * A1
#&gt; 
#&gt; Data:
#&gt; 170 observations of 2 variable(s) grouped in 5 datasets
#&gt; 
#&gt; Likelihood computed by importance sampling
#&gt;                           
#&gt; LL by is "-407.78 (df=13)"
#&gt;     AIC   BIC logLik
#&gt;   841.6 836.5 -407.8
#&gt; 
#&gt; Fitted parameters:
#&gt;                     estimate    lower   upper
#&gt; parent_0            93.76647 91.15312 96.3798
#&gt; log_k_A1            -6.13235 -8.45788 -3.8068
#&gt; f_parent_qlogis     -0.97364 -1.36940 -0.5779
#&gt; log_k1              -2.53176 -3.80372 -1.2598
#&gt; log_k2              -3.58667 -5.29524 -1.8781
#&gt; g_qlogis             0.01238 -1.07968  1.1044
#&gt; Var.parent_0         7.61106 -3.34955 18.5717
#&gt; Var.log_k_A1         4.64679 -2.73133 12.0249
#&gt; Var.f_parent_qlogis  0.19693 -0.05498  0.4488
#&gt; Var.log_k1           2.01717 -0.51980  4.5542
#&gt; Var.log_k2           3.63412 -0.92964  8.1979
#&gt; Var.g_qlogis         0.20045 -0.97425  1.3751
#&gt; a.1                  1.88335  1.66636  2.1004
#&gt; SD.parent_0          2.75881  0.77234  4.7453
#&gt; SD.log_k_A1          2.15564  0.44429  3.8670
#&gt; SD.f_parent_qlogis   0.44377  0.15994  0.7276
#&gt; SD.log_k1            1.42027  0.52714  2.3134
#&gt; SD.log_k2            1.90634  0.70934  3.1033
#&gt; SD.g_qlogis          0.44771 -0.86417  1.7596</div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/plot-SaemixObject-method.html'>plot</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span><span class='op'>)</span>
</div><div class='img'><img src='saem-5.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='https://rdrr.io/pkg/saemix/man/summary-methods.html'>summary</a></span><span class='op'>(</span><span class='va'>f_saem_dfop_sfo</span>, data <span class='op'>=</span> <span class='cn'>FALSE</span><span class='op'>)</span>
</div><div class='output co'>#&gt;                           
#&gt; LL by is "-407.78 (df=13)"</div><div class='output co'>#&gt; saemix version used for fitting:      3.1.9000 
#&gt; mkin version used for pre-fitting:  0.9.50.4 
#&gt; R version used for fitting:         4.0.3 
#&gt; Date of fit:     Wed Nov 11 19:48:33 2020 
#&gt; Date of summary: Wed Nov 11 19:48:33 2020 
#&gt; 
#&gt; Equations:
#&gt; d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
#&gt;            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 * time)))
#&gt;            * parent
#&gt; d_A1/dt = + f_parent_to_A1 * ((k1 * g * exp(-k1 * time) + k2 * (1 - g)
#&gt;            * exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
#&gt;            exp(-k2 * time))) * parent - k_A1 * A1
#&gt; 
#&gt; Data:
#&gt; 170 observations of 2 variable(s) grouped in 5 datasets
#&gt; 
#&gt; Model predictions using solution type analytical 
#&gt; 
#&gt; Fitted in 9.564 s using 300, 100 iterations
#&gt; 
#&gt; Variance model: Constant variance 
#&gt; 
#&gt; Mean of starting values for individual parameters:
#&gt;        parent_0        log_k_A1 f_parent_qlogis          log_k1          log_k2 
#&gt;      93.8101519      -9.7647455      -0.9711148      -1.8799371      -4.2708142 
#&gt;        g_qlogis 
#&gt;       0.1356441 
#&gt; 
#&gt; Fixed degradation parameter values:
#&gt; None
#&gt; 
#&gt; Results:
#&gt; 
#&gt; Likelihood computed by importance sampling
#&gt;     AIC   BIC logLik
#&gt;   841.6 836.5 -407.8
#&gt; 
#&gt; Optimised, transformed parameters with symmetric confidence intervals:
#&gt;                     est.  lower   upper
#&gt; parent_0        93.76647 91.153 96.3798
#&gt; log_k_A1        -6.13235 -8.458 -3.8068
#&gt; f_parent_qlogis -0.97364 -1.369 -0.5779
#&gt; log_k1          -2.53176 -3.804 -1.2598
#&gt; log_k2          -3.58667 -5.295 -1.8781
#&gt; g_qlogis         0.01238 -1.080  1.1044
#&gt; 
#&gt; Correlation: 
#&gt;                 prnt_0 lg__A1 f_prn_ log_k1 log_k2
#&gt; log_k_A1        -0.013                            
#&gt; f_parent_qlogis -0.025  0.050                     
#&gt; log_k1           0.030  0.000 -0.005              
#&gt; log_k2           0.010  0.005 -0.003  0.032       
#&gt; g_qlogis        -0.063 -0.015  0.010 -0.167 -0.177
#&gt; 
#&gt; Random effects:
#&gt;                      est.   lower  upper
#&gt; SD.parent_0        2.7588  0.7723 4.7453
#&gt; SD.log_k_A1        2.1556  0.4443 3.8670
#&gt; SD.f_parent_qlogis 0.4438  0.1599 0.7276
#&gt; SD.log_k1          1.4203  0.5271 2.3134
#&gt; SD.log_k2          1.9063  0.7093 3.1033
#&gt; SD.g_qlogis        0.4477 -0.8642 1.7596
#&gt; 
#&gt; Variance model:
#&gt;      est. lower upper
#&gt; a.1 1.883 1.666   2.1
#&gt; 
#&gt; Backtransformed parameters with asymmetric confidence intervals:
#&gt;                     est.     lower    upper
#&gt; parent_0       93.766473 9.115e+01 96.37983
#&gt; k_A1            0.002171 2.122e-04  0.02222
#&gt; f_parent_to_A1  0.274156 2.027e-01  0.35942
#&gt; k1              0.079519 2.229e-02  0.28371
#&gt; k2              0.027691 5.015e-03  0.15288
#&gt; g               0.503095 2.536e-01  0.75109
#&gt; 
#&gt; Resulting formation fractions:
#&gt;                 ff
#&gt; parent_A1   0.2742
#&gt; parent_sink 0.7258
#&gt; 
#&gt; Estimated disappearance times:
#&gt;          DT50    DT90 DT50back DT50_k1 DT50_k2
#&gt; parent  14.11   59.53    17.92   8.717   25.03
#&gt; A1     319.21 1060.38       NA      NA      NA</div><div class='input'>
<span class='co'># Using a single core, the following takes about 6 minutes as we do not have an</span>
<span class='co'># analytical solution. Using 10 cores it is slower instead of faster</span>
<span class='co'>#f_saem_fomc &lt;- saem(f_mmkin["FOMC-SFO", ], cores = 1)</span>
<span class='co'># }</span>
</div></pre>
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