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+++ b/docs/reference/mkinfit.html
@@ -1,5 +1,5 @@
<!DOCTYPE html>
-<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="This function maximises the likelihood of the observed data using the Port
+<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><title>Fit a kinetic model to data with one or more state variables — mkinfit • mkin</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.3.1/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.3.1/bootstrap.bundle.min.js"></script><link href="../deps/font-awesome-6.5.2/css/all.min.css" rel="stylesheet"><link href="../deps/font-awesome-6.5.2/css/v4-shims.min.css" rel="stylesheet"><script src="../deps/headroom-0.11.0/headroom.min.js"></script><script src="../deps/headroom-0.11.0/jQuery.headroom.min.js"></script><script src="../deps/bootstrap-toc-1.0.1/bootstrap-toc.min.js"></script><script src="../deps/clipboard.js-2.0.11/clipboard.min.js"></script><script src="../deps/search-1.0.0/autocomplete.jquery.min.js"></script><script src="../deps/search-1.0.0/fuse.min.js"></script><script src="../deps/search-1.0.0/mark.min.js"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Fit a kinetic model to data with one or more state variables — mkinfit"><meta name="description" content="This function maximises the likelihood of the observed data using the Port
algorithm stats::nlminb(), and the specified initial or fixed
parameters and starting values. In each step of the optimisation, the
kinetic model is solved using the function mkinpredict(), except
@@ -7,7 +7,7 @@ if an analytical solution is implemented, in which case the model is solved
using the degradation function in the mkinmod object. The
parameters of the selected error model are fitted simultaneously with the
degradation model parameters, as both of them are arguments of the
-likelihood function."><title>Fit a kinetic model to data with one or more state variables — mkinfit • mkin</title><script src="../deps/jquery-3.6.0/jquery-3.6.0.min.js"></script><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><link href="../deps/bootstrap-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Fit a kinetic model to data with one or more state variables — mkinfit"><meta property="og:description" content="This function maximises the likelihood of the observed data using the Port
+likelihood function."><meta property="og:description" content="This function maximises the likelihood of the observed data using the Port
algorithm stats::nlminb(), and the specified initial or fixed
parameters and starting values. In each step of the optimisation, the
kinetic model is solved using the function mkinpredict(), except
@@ -15,76 +15,63 @@ if an analytical solution is implemented, in which case the model is solved
using the degradation function in the mkinmod object. The
parameters of the selected error model are fitted simultaneously with the
degradation model parameters, as both of them are arguments of the
-likelihood function."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
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- <img src="" class="logo" alt=""><h1>Fit a kinetic model to data with one or more state variables</h1>
+
+ <h1>Fit a kinetic model to data with one or more state variables</h1>
<small class="dont-index">Source: <a href="https://github.com/jranke/mkin/blob/HEAD/R/mkinfit.R" class="external-link"><code>R/mkinfit.R</code></a></small>
<div class="d-none name"><code>mkinfit.Rd</code></div>
</div>
@@ -134,7 +121,9 @@ likelihood function.</p>
<div class="section level2">
<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
- <dl><dt>mkinmod</dt>
+
+
+<dl><dt id="arg-mkinmod">mkinmod<a class="anchor" aria-label="anchor" href="#arg-mkinmod"></a></dt>
<dd><p>A list of class <a href="mkinmod.html">mkinmod</a>, containing the kinetic
model to be fitted to the data, or one of the shorthand names ("SFO",
"FOMC", "DFOP", "HS", "SFORB", "IORE"). If a shorthand name is given, a
@@ -142,8 +131,9 @@ parent only degradation model is generated for the variable with the
highest value in <code>observed</code>.</p></dd>
-<dt>observed</dt>
-<dd><p>A dataframe with the observed data. The first column called
+<dt id="arg-observed">observed<a class="anchor" aria-label="anchor" href="#arg-observed"></a></dt>
+<dd><p>A dataframe or an object coercible to a dataframe
+(e.g. a <code>tibble</code>) with the observed data. The first column called
"name" must contain the name of the observed variable for each data point.
The second column must contain the times of observation, named "time".
The third column must be named "value" and contain the observed values.
@@ -154,7 +144,7 @@ not observed in degradation data, because there is a lower limit of
detection.</p></dd>
-<dt>parms.ini</dt>
+<dt id="arg-parms-ini">parms.ini<a class="anchor" aria-label="anchor" href="#arg-parms-ini"></a></dt>
<dd><p>A named vector of initial values for the parameters,
including parameters to be optimised and potentially also fixed parameters
as indicated by <code>fixed_parms</code>. If set to "auto", initial values for
@@ -167,7 +157,7 @@ this model. This works nicely if the models are nested. An example is
given below.</p></dd>
-<dt>state.ini</dt>
+<dt id="arg-state-ini">state.ini<a class="anchor" aria-label="anchor" href="#arg-state-ini"></a></dt>
<dd><p>A named vector of initial values for the state variables of
the model. In case the observed variables are represented by more than one
model variable, the names will differ from the names of the observed
@@ -178,27 +168,27 @@ others to 0. If this variable has no time zero observations, its initial
value is set to 100.</p></dd>
-<dt>err.ini</dt>
+<dt id="arg-err-ini">err.ini<a class="anchor" aria-label="anchor" href="#arg-err-ini"></a></dt>
<dd><p>A named vector of initial values for the error model
parameters to be optimised. If set to "auto", initial values are set to
default values. Otherwise, inital values for all error model parameters
must be given.</p></dd>
-<dt>fixed_parms</dt>
+<dt id="arg-fixed-parms">fixed_parms<a class="anchor" aria-label="anchor" href="#arg-fixed-parms"></a></dt>
<dd><p>The names of parameters that should not be optimised but
rather kept at the values specified in <code>parms.ini</code>. Alternatively,
a named numeric vector of parameters to be fixed, regardless of the values
in parms.ini.</p></dd>
-<dt>fixed_initials</dt>
+<dt id="arg-fixed-initials">fixed_initials<a class="anchor" aria-label="anchor" href="#arg-fixed-initials"></a></dt>
<dd><p>The names of model variables for which the initial
state at time 0 should be excluded from the optimisation. Defaults to all
state variables except for the first one.</p></dd>
-<dt>from_max_mean</dt>
+<dt id="arg-from-max-mean">from_max_mean<a class="anchor" aria-label="anchor" href="#arg-from-max-mean"></a></dt>
<dd><p>If this is set to TRUE, and the model has only one
observed variable, then data before the time of the maximum observed value
(after averaging for each sampling time) are discarded, and this time is
@@ -206,7 +196,7 @@ subtracted from all remaining time values, so the time of the maximum
observed mean value is the new time zero.</p></dd>
-<dt>solution_type</dt>
+<dt id="arg-solution-type">solution_type<a class="anchor" aria-label="anchor" href="#arg-solution-type"></a></dt>
<dd><p>If set to "eigen", the solution of the system of
differential equations is based on the spectral decomposition of the
coefficient matrix in cases that this is possible. If set to "deSolve", a
@@ -218,23 +208,23 @@ compiler is present, and "eigen" if no compiler is present and the model
can be expressed using eigenvalues and eigenvectors.</p></dd>
-<dt>method.ode</dt>
+<dt id="arg-method-ode">method.ode<a class="anchor" aria-label="anchor" href="#arg-method-ode"></a></dt>
<dd><p>The solution method passed via <code><a href="mkinpredict.html">mkinpredict()</a></code>
to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code> in case the solution type is "deSolve". The default
"lsoda" is performant, but sometimes fails to converge.</p></dd>
-<dt>use_compiled</dt>
+<dt id="arg-use-compiled">use_compiled<a class="anchor" aria-label="anchor" href="#arg-use-compiled"></a></dt>
<dd><p>If set to <code>FALSE</code>, no compiled version of the
<a href="mkinmod.html">mkinmod</a> model is used in the calls to <code><a href="mkinpredict.html">mkinpredict()</a></code> even if a compiled
version is present.</p></dd>
-<dt>control</dt>
+<dt id="arg-control">control<a class="anchor" aria-label="anchor" href="#arg-control"></a></dt>
<dd><p>A list of control arguments passed to <code><a href="https://rdrr.io/r/stats/nlminb.html" class="external-link">stats::nlminb()</a></code>.</p></dd>
-<dt>transform_rates</dt>
+<dt id="arg-transform-rates">transform_rates<a class="anchor" aria-label="anchor" href="#arg-transform-rates"></a></dt>
<dd><p>Boolean specifying if kinetic rate constants should
be transformed in the model specification used in the fitting for better
compliance with the assumption of normal distribution of the estimator. If
@@ -244,7 +234,7 @@ models and the break point tb of the HS model. If FALSE, zero is used as
a lower bound for the rates in the optimisation.</p></dd>
-<dt>transform_fractions</dt>
+<dt id="arg-transform-fractions">transform_fractions<a class="anchor" aria-label="anchor" href="#arg-transform-fractions"></a></dt>
<dd><p>Boolean specifying if formation fractions
should be transformed in the model specification used in the fitting for
better compliance with the assumption of normal distribution of the
@@ -253,23 +243,23 @@ the g parameter of the DFOP model is also transformed. Transformations
are described in <a href="transform_odeparms.html">transform_odeparms</a>.</p></dd>
-<dt>quiet</dt>
+<dt id="arg-quiet">quiet<a class="anchor" aria-label="anchor" href="#arg-quiet"></a></dt>
<dd><p>Suppress printing out the current value of the negative
log-likelihood after each improvement?</p></dd>
-<dt>atol</dt>
+<dt id="arg-atol">atol<a class="anchor" aria-label="anchor" href="#arg-atol"></a></dt>
<dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default
is 1e-8, which is lower than the default in the <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>
function which is used per default.</p></dd>
-<dt>rtol</dt>
+<dt id="arg-rtol">rtol<a class="anchor" aria-label="anchor" href="#arg-rtol"></a></dt>
<dd><p>Absolute error tolerance, passed to <code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>. Default
is 1e-10, much lower than in <code><a href="https://rdrr.io/pkg/deSolve/man/lsoda.html" class="external-link">deSolve::lsoda()</a></code>.</p></dd>
-<dt>error_model</dt>
+<dt id="arg-error-model">error_model<a class="anchor" aria-label="anchor" href="#arg-error-model"></a></dt>
<dd><p>If the error model is "const", a constant standard
deviation is assumed.</p>
<p>If the error model is "obs", each observed variable is assumed to have its
@@ -282,7 +272,7 @@ that the errors follow a lognormal distribution for large values, not a
normal distribution as assumed by this method.</p></dd>
-<dt>error_model_algorithm</dt>
+<dt id="arg-error-model-algorithm">error_model_algorithm<a class="anchor" aria-label="anchor" href="#arg-error-model-algorithm"></a></dt>
<dd><p>If "auto", the selected algorithm depends on
the error model. If the error model is "const", unweighted nonlinear
least squares fitting ("OLS") is selected. If the error model is "obs", or
@@ -309,33 +299,31 @@ using those error model parameters, until the error model parameters
converge.</p></dd>
-<dt>reweight.tol</dt>
+<dt id="arg-reweight-tol">reweight.tol<a class="anchor" aria-label="anchor" href="#arg-reweight-tol"></a></dt>
<dd><p>Tolerance for the convergence criterion calculated from
the error model parameters in IRLS fits.</p></dd>
-<dt>reweight.max.iter</dt>
+<dt id="arg-reweight-max-iter">reweight.max.iter<a class="anchor" aria-label="anchor" href="#arg-reweight-max-iter"></a></dt>
<dd><p>Maximum number of iterations in IRLS fits.</p></dd>
-<dt>trace_parms</dt>
+<dt id="arg-trace-parms">trace_parms<a class="anchor" aria-label="anchor" href="#arg-trace-parms"></a></dt>
<dd><p>Should a trace of the parameter values be listed?</p></dd>
-<dt>test_residuals</dt>
+<dt id="arg-test-residuals">test_residuals<a class="anchor" aria-label="anchor" href="#arg-test-residuals"></a></dt>
<dd><p>Should the residuals be tested for normal distribution?</p></dd>
-<dt>...</dt>
+<dt id="arg--">...<a class="anchor" aria-label="anchor" href="#arg--"></a></dt>
<dd><p>Further arguments that will be passed on to
<code><a href="https://rdrr.io/pkg/deSolve/man/ode.html" class="external-link">deSolve::ode()</a></code>.</p></dd>
</dl></div>
<div class="section level2">
<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
-
-
-<p>A list with "mkinfit" in the class attribute.</p>
+ <p>A list with "mkinfit" in the class attribute.</p>
</div>
<div class="section level2">
<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
@@ -378,10 +366,10 @@ Degradation Data. <em>Environments</em> 6(12) 124
<span class="r-in"><span><span class="co"># Use shorthand notation for parent only degradation</span></span></span>
<span class="r-in"><span><span class="va">fit</span> <span class="op">&lt;-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_C</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> mkin version used for fitting: 1.2.6 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> R version used for fitting: 4.3.2 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Date of fit: Thu Nov 16 04:15:31 2023 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Date of summary: Thu Nov 16 04:15:31 2023 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> mkin version used for fitting: 1.2.9 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> R version used for fitting: 4.4.2 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Date of fit: Thu Feb 13 14:56:49 2025 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Date of summary: Thu Feb 13 14:56:49 2025 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Equations:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span>
@@ -529,9 +517,9 @@ Degradation Data. <em>Environments</em> 6(12) 124
<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"analytical"</span><span class="op">)</span><span class="op">)</span></span></span>
<span class="r-in"><span><span class="op">}</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> test relative elapsed</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 3 analytical 1.000 0.223</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 2 eigen 1.973 0.440</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> 1 deSolve_compiled 2.072 0.462</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 3 analytical 1.000 0.227</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 2 eigen 1.930 0.438</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> 1 deSolve_compiled 1.991 0.452</span>
<span class="r-in"><span><span class="co"># }</span></span></span>
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="co"># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span></span></span>
@@ -556,12 +544,11 @@ Degradation Data. <em>Environments</em> 6(12) 124
<span class="r-in"><span><span class="co"># and beta indicate overparameterisation</span></span></span>
<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/r/base/summary.html" class="external-link">summary</a></span><span class="op">(</span><span class="va">fit.FOMC_SFO.tc</span>, data <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></span>
<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>NaNs produced</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>NaNs produced</span>
-<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>diag(.) had 0 or NA entries; non-finite result is doubtful</span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> mkin version used for fitting: 1.2.6 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> R version used for fitting: 4.3.2 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Date of fit: Thu Nov 16 04:15:35 2023 </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Date of summary: Thu Nov 16 04:15:35 2023 </span>
+<span class="r-wrn co"><span class="r-pr">#&gt;</span> <span class="warning">Warning: </span>diag(V) had non-positive or NA entries; the non-finite result may be dubious</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> mkin version used for fitting: 1.2.9 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> R version used for fitting: 4.4.2 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Date of fit: Thu Feb 13 14:56:53 2025 </span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Date of summary: Thu Feb 13 14:56:53 2025 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Equations:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span>
@@ -570,7 +557,7 @@ Degradation Data. <em>Environments</em> 6(12) 124
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Model predictions using solution type deSolve </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
-<span class="r-out co"><span class="r-pr">#&gt;</span> Fitted using 4062 model solutions performed in 0.768 s</span>
+<span class="r-out co"><span class="r-pr">#&gt;</span> Fitted using 4062 model solutions performed in 0.751 s</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Error model: Two-component variance function </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
@@ -670,23 +657,23 @@ Degradation Data. <em>Environments</em> 6(12) 124
<span class="r-in"><span><span class="co"># }</span></span></span>
</code></pre></div>
</div>
- </main><aside class="col-md-3"><nav id="toc"><h2>On this page</h2>
+ </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2>
</nav></aside></div>
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- <p></p><p>Developed by Johannes Ranke.</p>
+ <p>Developed by Johannes Ranke.</p>
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<div class="pkgdown-footer-right">
- <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
+ <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p>
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