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| author | Johannes Ranke <jranke@uni-bremen.de> | 2022-08-10 13:21:34 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2022-08-10 13:21:34 +0200 |
| commit | 9ee3d9f025ec7f5effddb0bcf9cf6e054c99794b (patch) | |
| tree | 3ea151f52dbc17b85839100b5639d64301460d5e /docs/reference/mkinfit.html | |
| parent | 9e346fabe99de71b21ef085be102027cfa774910 (diff) | |
Update static docs
Diffstat (limited to 'docs/reference/mkinfit.html')
| -rw-r--r-- | docs/reference/mkinfit.html | 304 |
1 files changed, 178 insertions, 126 deletions
diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html index e5bf1203..3b27ac7f 100644 --- a/docs/reference/mkinfit.html +++ b/docs/reference/mkinfit.html @@ -25,7 +25,7 @@ likelihood function."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ </button> <span class="navbar-brand"> <a class="navbar-link" href="../index.html">mkin</a> - <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.0</span> + <span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.1.2</span> </span> </div> @@ -103,33 +103,33 @@ likelihood function.</p> </div> <div id="ref-usage"> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="fu">mkinfit</span><span class="op">(</span> - <span class="va">mkinmod</span>, - <span class="va">observed</span>, - parms.ini <span class="op">=</span> <span class="st">"auto"</span>, - state.ini <span class="op">=</span> <span class="st">"auto"</span>, - err.ini <span class="op">=</span> <span class="st">"auto"</span>, - fixed_parms <span class="op">=</span> <span class="cn">NULL</span>, - fixed_initials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">diffs</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>, - from_max_mean <span class="op">=</span> <span class="cn">FALSE</span>, - solution_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"analytical"</span>, <span class="st">"eigen"</span>, <span class="st">"deSolve"</span><span class="op">)</span>, - method.ode <span class="op">=</span> <span class="st">"lsoda"</span>, - use_compiled <span class="op">=</span> <span class="st">"auto"</span>, - control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>eval.max <span class="op">=</span> <span class="fl">300</span>, iter.max <span class="op">=</span> <span class="fl">200</span><span class="op">)</span>, - transform_rates <span class="op">=</span> <span class="cn">TRUE</span>, - transform_fractions <span class="op">=</span> <span class="cn">TRUE</span>, - quiet <span class="op">=</span> <span class="cn">FALSE</span>, - atol <span class="op">=</span> <span class="fl">1e-08</span>, - rtol <span class="op">=</span> <span class="fl">1e-10</span>, - error_model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"obs"</span>, <span class="st">"tc"</span><span class="op">)</span>, - error_model_algorithm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"d_3"</span>, <span class="st">"direct"</span>, <span class="st">"twostep"</span>, <span class="st">"threestep"</span>, - <span class="st">"fourstep"</span>, <span class="st">"IRLS"</span>, <span class="st">"OLS"</span><span class="op">)</span>, - reweight.tol <span class="op">=</span> <span class="fl">1e-08</span>, - reweight.max.iter <span class="op">=</span> <span class="fl">10</span>, - trace_parms <span class="op">=</span> <span class="cn">FALSE</span>, - test_residuals <span class="op">=</span> <span class="cn">FALSE</span>, - <span class="va">...</span> -<span class="op">)</span></code></pre></div> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">mkinfit</span><span class="op">(</span></span> +<span> <span class="va">mkinmod</span>,</span> +<span> <span class="va">observed</span>,</span> +<span> parms.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> state.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> err.ini <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> fixed_parms <span class="op">=</span> <span class="cn">NULL</span>,</span> +<span> fixed_initials <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/names.html" class="external-link">names</a></span><span class="op">(</span><span class="va">mkinmod</span><span class="op">$</span><span class="va">diffs</span><span class="op">)</span><span class="op">[</span><span class="op">-</span><span class="fl">1</span><span class="op">]</span>,</span> +<span> from_max_mean <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> solution_type <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"analytical"</span>, <span class="st">"eigen"</span>, <span class="st">"deSolve"</span><span class="op">)</span>,</span> +<span> method.ode <span class="op">=</span> <span class="st">"lsoda"</span>,</span> +<span> use_compiled <span class="op">=</span> <span class="st">"auto"</span>,</span> +<span> control <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>eval.max <span class="op">=</span> <span class="fl">300</span>, iter.max <span class="op">=</span> <span class="fl">200</span><span class="op">)</span>,</span> +<span> transform_rates <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> transform_fractions <span class="op">=</span> <span class="cn">TRUE</span>,</span> +<span> quiet <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> atol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> rtol <span class="op">=</span> <span class="fl">1e-10</span>,</span> +<span> error_model <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"const"</span>, <span class="st">"obs"</span>, <span class="st">"tc"</span><span class="op">)</span>,</span> +<span> error_model_algorithm <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"auto"</span>, <span class="st">"d_3"</span>, <span class="st">"direct"</span>, <span class="st">"twostep"</span>, <span class="st">"threestep"</span>, <span class="st">"fourstep"</span>,</span> +<span> <span class="st">"IRLS"</span>, <span class="st">"OLS"</span><span class="op">)</span>,</span> +<span> reweight.tol <span class="op">=</span> <span class="fl">1e-08</span>,</span> +<span> reweight.max.iter <span class="op">=</span> <span class="fl">10</span>,</span> +<span> trace_parms <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> test_residuals <span class="op">=</span> <span class="cn">FALSE</span>,</span> +<span> <span class="va">...</span></span> +<span><span class="op">)</span></span></code></pre></div> </div> <div id="arguments"> @@ -140,6 +140,8 @@ 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 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 "name" must contain the name of the observed variable for each data point. @@ -150,6 +152,8 @@ order to avoid problems with fitting the two-component error model. This is not expected to be a problem, because in general, values of zero are not observed in degradation data, because there is a lower limit of detection.</p></dd> + + <dt>parms.ini</dt> <dd><p>A named vector of initial values for the parameters, including parameters to be optimised and potentially also fixed parameters @@ -161,6 +165,8 @@ needs. You can use the parameter lists "bparms.ode" from a previously fitted model, which contains the differential equation parameters from this model. This works nicely if the models are nested. An example is given below.</p></dd> + + <dt>state.ini</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 @@ -170,26 +176,36 @@ is to set the initial value of the first model variable to the mean of the time zero values for the variable with the maximum observed value, and all others to 0. If this variable has no time zero observations, its initial value is set to 100.</p></dd> + + <dt>err.ini</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> <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> <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> <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 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> <dd><p>If set to "eigen", the solution of the system of differential equations is based on the spectral decomposition of the @@ -200,16 +216,24 @@ only implemented for relatively simple degradation models. The default is "auto", which uses "analytical" if possible, otherwise "deSolve" if a 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> <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> <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> <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> <dd><p>Boolean specifying if kinetic rate constants should be transformed in the model specification used in the fitting for better @@ -218,6 +242,8 @@ TRUE, also alpha and beta parameters of the FOMC model are log-transformed, as well as k1 and k2 rate constants for the DFOP and HS 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> <dd><p>Boolean specifying if formation fractions should be transformed in the model specification used in the fitting for @@ -225,16 +251,24 @@ better compliance with the assumption of normal distribution of the estimator. The default (TRUE) is to do transformations. If TRUE, 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> <dd><p>Suppress printing out the current value of the negative log-likelihood after each improvement?</p></dd> + + <dt>atol</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> <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> <dd><p>If the error model is "const", a constant standard deviation is assumed.</p> @@ -246,6 +280,8 @@ used for setting up the likelihood function. Note that this model deviates from the model by Rocke and Lorenzato, as their model implies 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> <dd><p>If "auto", the selected algorithm depends on the error model. If the error model is "const", unweighted nonlinear @@ -271,22 +307,35 @@ unweighted least squares, and then iterates optimization of the error model parameters and subsequent optimization of the degradation model using those error model parameters, until the error model parameters converge.</p></dd> + + <dt>reweight.tol</dt> <dd><p>Tolerance for the convergence criterion calculated from the error model parameters in IRLS fits.</p></dd> + + <dt>reweight.max.iter</dt> <dd><p>Maximum number of iterations in IRLS fits.</p></dd> + + <dt>trace_parms</dt> <dd><p>Should a trace of the parameter values be listed?</p></dd> + + <dt>test_residuals</dt> <dd><p>Should the residuals be tested for normal distribution?</p></dd> + + <dt>...</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 id="value"> <h2>Value</h2> - <p>A list with "mkinfit" in the class attribute.</p> + + +<p>A list with "mkinfit" in the class attribute.</p> </div> <div id="details"> <h2>Details</h2> @@ -325,21 +374,21 @@ Degradation Data. <em>Environments</em> 6(12) 124 <div id="ref-examples"> <h2>Examples</h2> - <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"></span> -<span class="r-in"><span class="co"># Use shorthand notation for parent only degradation</span></span> -<span class="r-in"><span class="va">fit</span> <span class="op"><-</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 class="r-in"><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 class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:37:57 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:37:57 2022 </span> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span></span></span> +<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"><-</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">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 13:14:25 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 13:14:25 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type analytical </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted using 222 model solutions performed in 0.041 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 222 model solutions performed in 0.046 s</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model: Constant variance </span> <span class="r-out co"><span class="r-pr">#></span> </span> @@ -374,10 +423,10 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_alpha log_beta sigma</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.770e-08</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha -1.565e-01 1.000e+00 9.564e-01 9.974e-08</span> -<span class="r-out co"><span class="r-pr">#></span> log_beta -3.142e-01 9.564e-01 1.000e+00 8.468e-08</span> -<span class="r-out co"><span class="r-pr">#></span> sigma 4.770e-08 9.974e-08 8.468e-08 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 -1.565e-01 -3.142e-01 4.772e-08</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha -1.565e-01 1.000e+00 9.564e-01 1.005e-07</span> +<span class="r-out co"><span class="r-pr">#></span> log_beta -3.142e-01 9.564e-01 1.000e+00 8.541e-08</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 4.772e-08 1.005e-07 8.541e-08 1.000e+00</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> @@ -409,24 +458,24 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 63 parent 4.0 2.102 1.8977</span> <span class="r-out co"><span class="r-pr">#></span> 91 parent 3.9 1.441 2.4590</span> <span class="r-out co"><span class="r-pr">#></span> 119 parent 0.6 1.092 -0.4919</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># One parent compound, one metabolite, both single first order.</span></span> -<span class="r-in"><span class="co"># We remove zero values from FOCUS dataset D in order to avoid warnings</span></span> -<span class="r-in"><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span></span> -<span class="r-in"><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span> -<span class="r-in"> 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="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <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> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># One parent compound, one metabolite, both single first order.</span></span></span> +<span class="r-in"><span><span class="co"># We remove zero values from FOCUS dataset D in order to avoid warnings</span></span></span> +<span class="r-in"><span><span class="va">FOCUS_D</span> <span class="op"><-</span> <span class="fu"><a href="https://rdrr.io/r/base/subset.html" class="external-link">subset</a></span><span class="op">(</span><span class="va">FOCUS_2006_D</span>, <span class="va">value</span> <span class="op">!=</span> <span class="fl">0</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Use mkinsub for convenience in model formulation. Pathway to sink included per default.</span></span></span> +<span class="r-in"><span><span class="va">SFO_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><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="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <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></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># Fit the model quietly to the FOCUS example dataset D using defaults</span></span> -<span class="r-in"><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="fu"><a href="plot.mkinfit.html">plot_sep</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Fit the model quietly to the FOCUS example dataset D using defaults</span></span></span> +<span class="r-in"><span><span class="va">fit</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</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="plot.mkinfit.html">plot_sep</a></span><span class="op">(</span><span class="va">fit</span><span class="op">)</span></span></span> <span class="r-plt img"><img src="mkinfit-1.png" alt="" width="700" height="433"></span> -<span class="r-in"><span class="co"># As lower parent values appear to have lower variance, we try an alternative error model</span></span> -<span class="r-in"><span class="va">fit.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># This avoids the warning, and the likelihood ratio test confirms it is preferable</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># As lower parent values appear to have lower variance, we try an alternative error model</span></span></span> +<span class="r-in"><span><span class="va">fit.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This avoids the warning, and the likelihood ratio test confirms it is preferable</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -436,10 +485,10 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 2 5 -97.224 -1 64.483 9.737e-16 ***</span> <span class="r-out co"><span class="r-pr">#></span> ---</span> <span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> -<span class="r-in"><span class="co"># We can also allow for different variances of parent and metabolite as error model</span></span> -<span class="r-in"><span class="va">fit.obs</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># The two-component error model has significantly higher likelihood</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.obs</span>, <span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="co"># We can also allow for different variances of parent and metabolite as error model</span></span></span> +<span class="r-in"><span><span class="va">fit.obs</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"obs"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># The two-component error model has significantly higher likelihood</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.obs</span>, <span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: SFO_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -449,12 +498,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> 2 6 -96.936 0 63.907 < 2.2e-16 ***</span> <span class="r-out co"><span class="r-pr">#></span> ---</span> <span class="r-out co"><span class="r-pr">#></span> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1</span> -<span class="r-in"><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="parms.html">parms</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> parent_0 k_parent k_m1 f_parent_to_m1 sigma_low </span> <span class="r-out co"><span class="r-pr">#></span> 1.007343e+02 1.005562e-01 5.166712e-03 5.083933e-01 3.049883e-03 </span> <span class="r-out co"><span class="r-pr">#></span> rsd_high </span> <span class="r-out co"><span class="r-pr">#></span> 7.928118e-02 </span> -<span class="r-in"><span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="fu"><a href="endpoints.html">endpoints</a></span><span class="op">(</span><span class="va">fit.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> $ff</span> <span class="r-out co"><span class="r-pr">#></span> parent_m1 parent_sink </span> <span class="r-out co"><span class="r-pr">#></span> 0.5083933 0.4916067 </span> @@ -462,38 +511,41 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> $distimes</span> <span class="r-out co"><span class="r-pr">#></span> DT50 DT90</span> <span class="r-out co"><span class="r-pr">#></span> parent 6.89313 22.89848</span> -<span class="r-out co"><span class="r-pr">#></span> m1 134.15634 445.65770</span> -<span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># We can show a quick (only one replication) benchmark for this case, as we</span></span> -<span class="r-in"><span class="co"># have several alternative solution methods for the model. We skip</span></span> -<span class="r-in"><span class="co"># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span></span> -<span class="r-in"><span class="co"># benchmark vignette</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="kw">if</span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span> -<span class="r-in"> <span class="fu">benchmark</span><span class="op">(</span>replications <span class="op">=</span> <span class="fl">1</span>, order <span class="op">=</span> <span class="st">"relative"</span>, columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"test"</span>, <span class="st">"relative"</span>, <span class="st">"elapsed"</span><span class="op">)</span>,</span> -<span class="r-in"> deSolve_compiled <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, use_compiled <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span> -<span class="r-in"> eigen <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"eigen"</span><span class="op">)</span>,</span> -<span class="r-in"> analytical <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span> -<span class="r-in"> solution_type <span class="op">=</span> <span class="st">"analytical"</span><span class="op">)</span><span class="op">)</span></span> -<span class="r-in"><span class="op">}</span></span> +<span class="r-out co"><span class="r-pr">#></span> m1 134.15634 445.65772</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can show a quick (only one replication) benchmark for this case, as we</span></span></span> +<span class="r-in"><span><span class="co"># have several alternative solution methods for the model. We skip</span></span></span> +<span class="r-in"><span><span class="co"># uncompiled deSolve, as it is so slow. More benchmarks are found in the</span></span></span> +<span class="r-in"><span><span class="co"># benchmark vignette</span></span></span> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="kw">if</span><span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="va"><a href="http://rbenchmark.googlecode.com" class="external-link">rbenchmark</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/rbenchmark/man/benchmark.html" class="external-link">benchmark</a></span><span class="op">(</span>replications <span class="op">=</span> <span class="fl">1</span>, order <span class="op">=</span> <span class="st">"relative"</span>, columns <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span><span class="st">"test"</span>, <span class="st">"relative"</span>, <span class="st">"elapsed"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> deSolve_compiled <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"deSolve"</span>, use_compiled <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> eigen <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<span class="r-in"><span> solution_type <span class="op">=</span> <span class="st">"eigen"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> analytical <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">SFO_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span>,</span></span> +<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-msg co"><span class="r-pr">#></span> Loading required package: rbenchmark</span> -<span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>there is no package called ‘rbenchmark’</span> -<span class="r-in"><span class="co"># }</span></span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># Use stepwise fitting, using optimised parameters from parent only fit, FOMC-SFO</span></span> -<span class="r-in"><span class="co"># \dontrun{</span></span> -<span class="r-in"><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span> -<span class="r-in"> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span> -<span class="r-in"> m1 <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> +<span class="r-out co"><span class="r-pr">#></span> test relative elapsed</span> +<span class="r-out co"><span class="r-pr">#></span> 3 analytical 1.000 0.540</span> +<span class="r-out co"><span class="r-pr">#></span> 1 deSolve_compiled 1.537 0.830</span> +<span class="r-out co"><span class="r-pr">#></span> 2 eigen 2.687 1.451</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> +<span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="va">FOMC_SFO</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span></span></span> +<span class="r-in"><span> parent <span class="op">=</span> <span class="fu"><a href="mkinmod.html">mkinsub</a></span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="st">"m1"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> m1 <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></span> <span class="r-msg co"><span class="r-pr">#></span> Temporary DLL for differentials generated and loaded</span> -<span class="r-in"><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># Again, we get a warning and try a more sophisticated error model</span></span> -<span class="r-in"><span class="va">fit.FOMC_SFO.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># This model has a higher likelihood, but not significantly so</span></span> -<span class="r-in"><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit.FOMC_SFO.tc</span><span class="op">)</span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># Again, we get a warning and try a more sophisticated error model</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO.tc</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># This model has a higher likelihood, but not significantly so</span></span></span> +<span class="r-in"><span><span class="fu"><a href="https://rdrr.io/pkg/lmtest/man/lrtest.html" class="external-link">lrtest</a></span><span class="op">(</span><span class="va">fit.tc</span>, <span class="va">fit.FOMC_SFO.tc</span><span class="op">)</span></span></span> <span class="r-out co"><span class="r-pr">#></span> Likelihood ratio test</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model 1: FOMC_SFO with error model tc and fixed parameter(s) m1_0</span> @@ -501,16 +553,16 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> #Df LogLik Df Chisq Pr(>Chisq)</span> <span class="r-out co"><span class="r-pr">#></span> 1 7 -64.829 </span> <span class="r-out co"><span class="r-pr">#></span> 2 6 -64.983 -1 0.3075 0.5792</span> -<span class="r-in"><span class="co"># Also, the missing standard error for log_beta and the t-tests for alpha</span></span> -<span class="r-in"><span class="co"># and beta indicate overparameterisation</span></span> -<span class="r-in"><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 class="r-in"><span><span class="co"># Also, the missing standard error for log_beta and the t-tests for alpha</span></span></span> +<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">#></span> <span class="warning">Warning: </span>NaNs produced</span> <span class="r-wrn co"><span class="r-pr">#></span> <span class="warning">Warning: </span>NaNs produced</span> <span class="r-wrn co"><span class="r-pr">#></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">#></span> mkin version used for fitting: 1.1.0 </span> -<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.0 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed May 18 20:38:07 2022 </span> -<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed May 18 20:38:07 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> mkin version used for fitting: 1.1.2 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.2.1 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Wed Aug 10 13:14:36 2022 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Wed Aug 10 13:14:36 2022 </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Equations:</span> <span class="r-out co"><span class="r-pr">#></span> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent</span> @@ -519,12 +571,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Model predictions using solution type deSolve </span> <span class="r-out co"><span class="r-pr">#></span> </span> -<span class="r-out co"><span class="r-pr">#></span> Fitted using 3924 model solutions performed in 7.107 s</span> +<span class="r-out co"><span class="r-pr">#></span> Fitted using 3729 model solutions performed in 2.488 s</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model: Two-component variance function </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Error model algorithm: d_3 </span> -<span class="r-out co"><span class="r-pr">#></span> Three-step fitting yielded a higher likelihood than direct fitting </span> +<span class="r-out co"><span class="r-pr">#></span> Direct fitting and three-step fitting yield approximately the same likelihood </span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Starting values for parameters to be optimised:</span> <span class="r-out co"><span class="r-pr">#></span> value type</span> @@ -559,7 +611,7 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> Estimate Std. Error Lower Upper</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 101.600000 2.6400000 96.240000 107.000000</span> <span class="r-out co"><span class="r-pr">#></span> log_k_m1 -5.284000 0.0929100 -5.474000 -5.095000</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.001426 0.0766900 -0.155000 0.157800</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.001426 0.0767000 -0.155000 0.157800</span> <span class="r-out co"><span class="r-pr">#></span> log_alpha 5.522000 0.0077320 5.506000 5.538000</span> <span class="r-out co"><span class="r-pr">#></span> log_beta 7.806000 NaN NaN NaN</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low 0.002488 0.0002431 0.001992 0.002984</span> @@ -567,31 +619,31 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Parameter correlation:</span> <span class="r-out co"><span class="r-pr">#></span> parent_0 log_k_m1 f_parent_qlogis log_alpha log_beta</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000000 -0.095145 -0.76674 0.70541 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.095145 1.000000 0.51428 -0.14381 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.766743 0.514278 1.00000 -0.61392 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.705413 -0.143809 -0.61392 1.00000 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000000 -0.095226 -0.76678 0.70544 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 -0.095226 1.000000 0.51432 -0.14387 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -0.766780 0.514321 1.00000 -0.61396 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 0.705444 -0.143872 -0.61396 1.00000 NaN</span> <span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN NaN NaN 1</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.016077 0.001586 0.01548 5.87034 NaN</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.006617 -0.011694 -0.05356 0.04848 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 0.016073 0.001586 0.01548 5.87007 NaN</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high 0.006626 -0.011700 -0.05357 0.04849 NaN</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low rsd_high</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 0.016077 0.006617</span> -<span class="r-out co"><span class="r-pr">#></span> log_k_m1 0.001586 -0.011694</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.015476 -0.053560</span> -<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.870339 0.048481</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 0.016073 0.006626</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_m1 0.001586 -0.011700</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.015476 -0.053566</span> +<span class="r-out co"><span class="r-pr">#></span> log_alpha 5.870075 0.048487</span> <span class="r-out co"><span class="r-pr">#></span> log_beta NaN NaN</span> -<span class="r-out co"><span class="r-pr">#></span> sigma_low 1.000000 -0.652555</span> -<span class="r-out co"><span class="r-pr">#></span> rsd_high -0.652555 1.000000</span> +<span class="r-out co"><span class="r-pr">#></span> sigma_low 1.000000 -0.652558</span> +<span class="r-out co"><span class="r-pr">#></span> rsd_high -0.652558 1.000000</span> <span class="r-out co"><span class="r-pr">#></span> </span> <span class="r-out co"><span class="r-pr">#></span> Backtransformed parameters:</span> <span class="r-out co"><span class="r-pr">#></span> Confidence intervals for internally transformed parameters are asymmetric.</span> <span class="r-out co"><span class="r-pr">#></span> t-test (unrealistically) based on the assumption of normal distribution</span> <span class="r-out co"><span class="r-pr">#></span> for estimators of untransformed parameters.</span> <span class="r-out co"><span class="r-pr">#></span> Estimate t value Pr(>t) Lower Upper</span> -<span class="r-out co"><span class="r-pr">#></span> parent_0 1.016e+02 32.7800 6.312e-26 9.624e+01 1.070e+02</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.016e+02 32.7800 6.311e-26 9.624e+01 1.070e+02</span> <span class="r-out co"><span class="r-pr">#></span> k_m1 5.072e-03 10.1200 1.216e-11 4.196e-03 6.130e-03</span> -<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 5.004e-01 20.8300 4.318e-20 4.613e-01 5.394e-01</span> -<span class="r-out co"><span class="r-pr">#></span> alpha 2.502e+02 0.5624 2.890e-01 2.463e+02 2.542e+02</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_m1 5.004e-01 20.8300 4.317e-20 4.613e-01 5.394e-01</span> +<span class="r-out co"><span class="r-pr">#></span> alpha 2.502e+02 0.5624 2.889e-01 2.463e+02 2.542e+02</span> <span class="r-out co"><span class="r-pr">#></span> beta 2.455e+03 0.5549 2.915e-01 NA NA</span> <span class="r-out co"><span class="r-pr">#></span> sigma_low 2.488e-03 0.4843 3.158e-01 1.992e-03 2.984e-03</span> <span class="r-out co"><span class="r-pr">#></span> rsd_high 7.921e-02 8.4300 8.001e-10 6.018e-02 9.823e-02</span> @@ -611,12 +663,12 @@ Degradation Data. <em>Environments</em> 6(12) 124 <span class="r-out co"><span class="r-pr">#></span> DT50 DT90 DT50back</span> <span class="r-out co"><span class="r-pr">#></span> parent 6.812 22.7 6.834</span> <span class="r-out co"><span class="r-pr">#></span> m1 136.661 454.0 NA</span> -<span class="r-in"></span> -<span class="r-in"><span class="co"># We can easily use starting parameters from the parent only fit (only for illustration)</span></span> -<span class="r-in"><span class="va">fit.FOMC</span> <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span> -<span class="r-in"> parms.ini <span class="op">=</span> <span class="va">fit.FOMC</span><span class="op">$</span><span class="va">bparms.ode</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span> -<span class="r-in"><span class="co"># }</span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># We can easily use starting parameters from the parent only fit (only for illustration)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC</span> <span class="op">=</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="st">"FOMC"</span>, <span class="va">FOCUS_2006_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="va">fit.FOMC_SFO</span> <span class="op"><-</span> <span class="fu">mkinfit</span><span class="op">(</span><span class="va">FOMC_SFO</span>, <span class="va">FOCUS_D</span>, quiet <span class="op">=</span> <span class="cn">TRUE</span>,</span></span> +<span class="r-in"><span> parms.ini <span class="op">=</span> <span class="va">fit.FOMC</span><span class="op">$</span><span class="va">bparms.ode</span>, error_model <span class="op">=</span> <span class="st">"tc"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="co"># }</span></span></span> </code></pre></div> </div> </div> @@ -631,7 +683,7 @@ Degradation Data. <em>Environments</em> 6(12) 124 </div> <div class="pkgdown"> - <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.3.</p> + <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.6.</p> </div> </footer></div> |