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have been obtained by fitting the same model to a list of datasets." />
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<h1>Create an nlme model for an mmkin row object</h1>
<div class="hidden name"><code>nlme.mmkin.Rd</code></div>
</div>
<div class="ref-description">
<p>This functions sets 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='co'># S3 method for mmkin</span>
<span class='fu'>nlme</span>(
<span class='no'>model</span>,
<span class='kw'>data</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/sys.parent.html'>sys.frame</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/sys.parent.html'>sys.parent</a></span>()),
<span class='no'>fixed</span>,
<span class='kw'>random</span> <span class='kw'>=</span> <span class='no'>fixed</span>,
<span class='no'>groups</span>,
<span class='no'>start</span>,
<span class='kw'>correlation</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>weights</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='no'>subset</span>,
<span class='kw'>method</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"ML"</span>, <span class='st'>"REML"</span>),
<span class='kw'>na.action</span> <span class='kw'>=</span> <span class='no'>na.fail</span>,
<span class='no'>naPattern</span>,
<span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(),
<span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>
)
<span class='co'># S3 method for nlme.mmkin</span>
<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='co'># S3 method for nlme.mmkin</span>
<span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>object</span>, <span class='no'>...</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>model</th>
<td><p>An <code><a href='mmkin.html'>mmkin</a></code> row object.</p></td>
</tr>
<tr>
<th>data</th>
<td><p>Should the data be printed?</p></td>
</tr>
<tr>
<th>fixed</th>
<td><p>Ignored, all degradation parameters fitted in the
mmkin model are used as fixed parameters</p></td>
</tr>
<tr>
<th>random</th>
<td><p>If not specified, all fixed effects are complemented
with uncorrelated random effects</p></td>
</tr>
<tr>
<th>groups</th>
<td><p>See the documentation of nlme</p></td>
</tr>
<tr>
<th>start</th>
<td><p>If not specified, mean values of the fitted degradation
parameters taken from the mmkin object are used</p></td>
</tr>
<tr>
<th>correlation</th>
<td><p>See the documentation of nlme</p></td>
</tr>
<tr>
<th>weights</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>subset</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>method</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>na.action</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>naPattern</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>control</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>verbose</th>
<td><p>passed to nlme</p></td>
</tr>
<tr>
<th>x</th>
<td><p>An nlme.mmkin object to print</p></td>
</tr>
<tr>
<th>...</th>
<td><p>Update specifications passed to update.nlme</p></td>
</tr>
<tr>
<th>object</th>
<td><p>An nlme.mmkin object to update</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Upon success, a fitted nlme.mmkin object, which is an nlme object
with additional elements</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.html'>nlme_function</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'>ds</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span>(<span class='no'>experimental_data_for_UBA_2019</span>[<span class='fl'>6</span>:<span class='fl'>10</span>],
<span class='kw'>function</span>(<span class='no'>x</span>) <span class='fu'><a href='https://rdrr.io/r/base/subset.html'>subset</a></span>(<span class='no'>x</span>$<span class='no'>data</span>[<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span>)], <span class='no'>name</span> <span class='kw'>==</span> <span class='st'>"parent"</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'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>)
<span class='fu'><a href='https://rdrr.io/r/base/library.html'>library</a></span>(<span class='no'>nlme</span>)
<span class='no'>f_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'>f</span>)
<span class='fu'><a href='https://rdrr.io/r/base/print.html'>print</a></span>(<span class='no'>f_nlme</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood
#> Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink)
#> Data: "Not shown"
#> Log-likelihood: -307.5269
#> Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
#> parent_0 log_k_parent_sink
#> 85.541149 -3.229596
#>
#> Random effects:
#> Formula: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
#> Level: ds
#> Structure: Diagonal
#> parent_0 log_k_parent_sink Residual
#> StdDev: 1.30857 1.288591 6.304906
#>
#> Number of Observations: 90
#> Number of Groups: 5 </div><div class='input'><span class='no'>f_nlme_2</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f</span>, <span class='kw'>start</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='kw'>parent_0</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>log_k_parent_sink</span> <span class='kw'>=</span> <span class='fl'>0.1</span>))
<span class='fu'><a href='https://rdrr.io/r/stats/update.html'>update</a></span>(<span class='no'>f_nlme_2</span>, <span class='kw'>random</span> <span class='kw'>=</span> <span class='no'>parent_0</span> ~ <span class='fl'>1</span>)</div><div class='output co'>#> Nonlinear mixed-effects model fit by maximum likelihood
#> Model: value ~ deg_func(name, time, parent_0, log_k_parent_sink)
#> Data: "Not shown"
#> Log-likelihood: -404.3729
#> Fixed: list(parent_0 ~ 1, log_k_parent_sink ~ 1)
#> parent_0 log_k_parent_sink
#> 75.933480 -3.555983
#>
#> Random effects:
#> Formula: parent_0 ~ 1 | ds
#> parent_0 Residual
#> StdDev: 0.002416792 21.63027
#>
#> Number of Observations: 90
#> Number of Groups: 5 </div><div class='input'><span class='co'># \dontrun{</span>
<span class='co'># Test on some real data</span>
<span class='no'>ds_2</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/r/base/lapply.html'>lapply</a></span>(<span class='no'>experimental_data_for_UBA_2019</span>[<span class='fl'>6</span>:<span class='fl'>10</span>],
<span class='kw'>function</span>(<span class='no'>x</span>) <span class='no'>x</span>$<span class='no'>data</span>[<span class='fu'><a href='https://rdrr.io/r/base/c.html'>c</a></span>(<span class='st'>"name"</span>, <span class='st'>"time"</span>, <span class='st'>"value"</span>)])
<span class='no'>m_sfo_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='st'>"A1"</span>),
<span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"min"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>m_sfo_sfo_ff</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='st'>"A1"</span>),
<span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>m_fomc_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'>"FOMC"</span>, <span class='st'>"A1"</span>),
<span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>m_dfop_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'>"DFOP"</span>, <span class='st'>"A1"</span>),
<span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>), <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='no'>f_2</span> <span class='kw'><-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='st'>"SFO-SFO"</span> <span class='kw'>=</span> <span class='no'>m_sfo_sfo</span>,
<span class='st'>"SFO-SFO-ff"</span> <span class='kw'>=</span> <span class='no'>m_sfo_sfo_ff</span>,
<span class='st'>"FOMC-SFO"</span> <span class='kw'>=</span> <span class='no'>m_fomc_sfo</span>,
<span class='st'>"DFOP-SFO"</span> <span class='kw'>=</span> <span class='no'>m_dfop_sfo</span>),
<span class='no'>ds_2</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>]) <span class='co'># Separate fits for datasets 3 and 4</span></div><div class='img'><img src='nlme.mmkin-1.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='no'>f_nlme_sfo_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO"</span>, ])
<span class='co'># plot(f_nlme_sfo_sfo) # not feasible with pkgdown figures</span>
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_sfo_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>) <span class='co'># Global mixed model: Fits for datasets 3 and 4</span></div><div class='img'><img src='nlme.mmkin-2.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># With formation fractions</span>
<span class='no'>f_nlme_sfo_sfo_ff</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"SFO-SFO-ff"</span>, ])
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_sfo_sfo_ff</span>, <span class='fl'>3</span>:<span class='fl'>4</span>) <span class='co'># chi2 different due to different df attribution</span></div><div class='img'><img src='nlme.mmkin-3.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># For more parameters, we need to increase pnlsMaxIter and the tolerance</span>
<span class='co'># to get convergence</span>
<span class='no'>f_nlme_fomc_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"FOMC-SFO"</span>, ],
<span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>pnlsMaxIter</span> <span class='kw'>=</span> <span class='fl'>100</span>, <span class='kw'>tolerance</span> <span class='kw'>=</span> <span class='fl'>1e-4</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#>
#> **Iteration 1
#> LME step: Loglik: -394.1603, nlminb iterations: 2
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5
#> -0.2079984 0.8563873 1.7454146 1.0917723 1.2756924
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 643.8786
#> fixed effects: 94.17379 -5.473199 -0.6970239 -0.2025094 2.103883
#> iterations: 100
#> Convergence crit. (must all become <= tolerance = 0.0001):
#> fixed reStruct
#> 0.7865373 0.1448077
#>
#> **Iteration 2
#> LME step: Loglik: -396.3824, nlminb iterations: 7
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5
#> -1.712408e-01 -2.680989e-05 1.842119e+00 1.073975e+00 1.322924e+00
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 643.8022
#> fixed effects: 94.17385 -5.473491 -0.6970405 -0.202514 2.103871
#> iterations: 100
#> Convergence crit. (must all become <= tolerance = 0.0001):
#> fixed reStruct
#> 5.341904e-05 1.227073e-03
#>
#> **Iteration 3
#> LME step: Loglik: -396.3825, nlminb iterations: 7
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5
#> -0.1712484347 -0.0001513555 1.8420964843 1.0739800649 1.3229176990
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 643.7947
#> fixed effects: 94.17386 -5.473522 -0.6970423 -0.2025142 2.10387
#> iterations: 100
#> Convergence crit. (must all become <= tolerance = 0.0001):
#> fixed reStruct
#> 5.568186e-06 1.276609e-04
#>
#> **Iteration 4
#> LME step: Loglik: -396.3825, nlminb iterations: 7
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5
#> -0.171251200 -0.000164506 1.842095097 1.073980200 1.322916184
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 643.7934
#> fixed effects: 94.17386 -5.473526 -0.6970426 -0.2025146 2.103869
#> iterations: 100
#> Convergence crit. (must all become <= tolerance = 0.0001):
#> fixed reStruct
#> 2.332100e-06 1.979007e-05 </div><div class='input'> <span class='no'>f_nlme_dfop_sfo</span> <span class='kw'><-</span> <span class='fu'><a href='https://rdrr.io/pkg/nlme/man/nlme.html'>nlme</a></span>(<span class='no'>f_2</span>[<span class='st'>"DFOP-SFO"</span>, ],
<span class='kw'>control</span> <span class='kw'>=</span> <span class='fu'><a href='https://rdrr.io/r/base/list.html'>list</a></span>(<span class='kw'>pnlsMaxIter</span> <span class='kw'>=</span> <span class='fl'>120</span>, <span class='kw'>tolerance</span> <span class='kw'>=</span> <span class='fl'>5e-4</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#>
#> **Iteration 1
#> LME step: Loglik: -404.9591, nlminb iterations: 1
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5 ds6
#> -0.4114594 0.9798456 1.6990016 0.7293119 0.3353829 1.7112922
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 630.391
#> fixed effects: 93.82265 -5.455841 -0.6788837 -1.862191 -4.199654 0.05531046
#> iterations: 120
#> Convergence crit. (must all become <= tolerance = 0.0005):
#> fixed reStruct
#> 0.7872619 0.5811683
#>
#> **Iteration 2
#> LME step: Loglik: -407.7755, nlminb iterations: 11
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5 ds6
#> -0.371222832 0.003084754 1.789952290 0.724634064 0.301559136 1.754244638
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 630.359
#> fixed effects: 93.82269 -5.456014 -0.6788967 -1.862202 -4.199678 0.05534118
#> iterations: 120
#> Convergence crit. (must all become <= tolerance = 0.0005):
#> fixed reStruct
#> 0.0005550885 0.0007749418
#>
#> **Iteration 3
#> LME step: Loglik: -407.7756, nlminb iterations: 11
#> reStruct parameters:
#> ds1 ds2 ds3 ds4 ds5 ds6
#> -0.371217033 0.003064156 1.789935045 0.724683005 0.301622307 1.754234135
#> Beginning PNLS step: .. completed fit_nlme() step.
#> PNLS step: RSS = 630.358
#> fixed effects: 93.82269 -5.456017 -0.6788969 -1.862197 -4.199677 0.05532978
#> iterations: 120
#> Convergence crit. (must all become <= tolerance = 0.0005):
#> fixed reStruct
#> 2.059533e-04 4.860085e-05 </div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"FOMC-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>])</div><div class='img'><img src='nlme.mmkin-4.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_fomc_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>)</div><div class='img'><img src='nlme.mmkin-5.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_2</span>[<span class='st'>"DFOP-SFO"</span>, <span class='fl'>3</span>:<span class='fl'>4</span>])</div><div class='img'><img src='nlme.mmkin-6.png' alt='' width='700' height='433' /></div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/graphics/plot.html'>plot</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='fl'>3</span>:<span class='fl'>4</span>)</div><div class='img'><img src='nlme.mmkin-7.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='no'>f_nlme_fomc_sfo</span>, <span class='no'>f_nlme_sfo_sfo</span>)</div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value
#> f_nlme_dfop_sfo 1 13 843.8541 884.6194 -408.9270
#> f_nlme_fomc_sfo 2 11 818.5149 853.0087 -398.2575 1 vs 2 21.33913 <.0001
#> f_nlme_sfo_sfo 3 9 1085.1821 1113.4042 -533.5910 2 vs 3 270.66712 <.0001</div><div class='input'> <span class='fu'><a href='https://rdrr.io/r/stats/anova.html'>anova</a></span>(<span class='no'>f_nlme_dfop_sfo</span>, <span class='no'>f_nlme_sfo_sfo</span>) <span class='co'># if we ignore FOMC</span></div><div class='output co'>#> Model df AIC BIC logLik Test L.Ratio p-value
#> f_nlme_dfop_sfo 1 13 843.8541 884.6194 -408.927
#> f_nlme_sfo_sfo 2 9 1085.1821 1113.4042 -533.591 1 vs 2 249.328 <.0001</div><div class='input'># }
</div></pre>
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