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diff --git a/docs/dev/reference/synthetic_data_for_UBA_2014.html b/docs/dev/reference/synthetic_data_for_UBA_2014.html new file mode 100644 index 00000000..9080c32b --- /dev/null +++ b/docs/dev/reference/synthetic_data_for_UBA_2014.html @@ -0,0 +1,413 @@ +<!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"><title>Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • 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="Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014"><meta name="description" content="The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites. +Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along. +Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to NA. +As an example, the first dataset has the title SFO_lin_a and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'. +Compare also the code in the example section to see the degradation models."><meta property="og:description" content="The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites. +Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along. +Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to NA. +As an example, the first dataset has the title SFO_lin_a and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'. +Compare also the code in the example section to see the degradation models."><meta name="robots" content="noindex"></head><body> + <a href="#main" class="visually-hidden-focusable">Skip to contents</a> + + + <nav class="navbar navbar-expand-lg fixed-top bg-light" data-bs-theme="default" aria-label="Site navigation"><div class="container"> + + <a class="navbar-brand me-2" href="../index.html">mkin</a> + + <small class="nav-text text-info me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="In-development version">1.2.10</small> + + + <button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation"> + <span class="navbar-toggler-icon"></span> + </button> + + <div id="navbar" class="collapse navbar-collapse ms-3"> + <ul class="navbar-nav me-auto"><li class="active nav-item"><a class="nav-link" href="../reference/index.html">Reference</a></li> +<li class="nav-item dropdown"> + <button class="nav-link dropdown-toggle" type="button" id="dropdown-articles" data-bs-toggle="dropdown" aria-expanded="false" aria-haspopup="true">Articles</button> + <ul class="dropdown-menu" aria-labelledby="dropdown-articles"><li><a class="dropdown-item" href="../articles/mkin.html">Introduction to mkin</a></li> + <li><hr class="dropdown-divider"></li> + 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dimethenamid and dimethenamid-P</a></li> + <li><a class="dropdown-item" href="../articles/prebuilt/2023_mesotrione_parent.html">Testing covariate modelling in hierarchical parent degradation kinetics with residue data on mesotrione</a></li> + <li><a class="dropdown-item" href="../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a></li> + <li><a class="dropdown-item" href="../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a></li> + <li><a class="dropdown-item" href="../articles/web_only/multistart.html">Short demo of the multistart method</a></li> + <li><hr class="dropdown-divider"></li> + <li><h6 class="dropdown-header" data-toc-skip>Performance</h6></li> + <li><a class="dropdown-item" href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a></li> + <li><a class="dropdown-item" 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placeholder="Search for" data-search-index="../search.json"></form></li> +<li class="nav-item"><a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="GitHub"><span class="fa fab fa-github fa-lg"></span></a></li> + </ul></div> + + + </div> +</nav><div class="container template-reference-topic"> +<div class="row"> + <main id="main" class="col-md-9"><div class="page-header"> + + <h1>Synthetic datasets for one parent compound with two metabolites</h1> + + <div class="d-none name"><code>synthetic_data_for_UBA_2014.Rd</code></div> + </div> + + <div class="ref-description section level2"> + <p>The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites.</p> +<p>Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y. Note that this is a simplified version + of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the + measured values approximates lognormal distribution for high values, whereas we are using + normally distributed error components all along.</p> +<p>Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to <code>NA</code>.</p> +<p>As an example, the first dataset has the title <code>SFO_lin_a</code> and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'.</p> +<p>Compare also the code in the example section to see the degradation models.</p> + </div> + + <div class="section level2"> + <h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span><span class="va">synthetic_data_for_UBA_2014</span></span></code></pre></div> + </div> + + <div class="section level2"> + <h2 id="format">Format<a class="anchor" aria-label="anchor" href="#format"></a></h2> + <p>A list containing twelve datasets as an R6 class defined by <code><a href="mkinds.html">mkinds</a></code>, + each containing, among others, the following components</p><dl><dt><code>title</code></dt> +<dd><p>The name of the dataset, e.g. <code>SFO_lin_a</code></p></dd> + + <dt><code>data</code></dt> +<dd><p>A data frame with the data in the form expected by <code><a href="mkinfit.html">mkinfit</a></code></p></dd> + + +</dl></div> + <div class="section level2"> + <h2 id="source">Source<a class="anchor" aria-label="anchor" href="#source"></a></h2> + <p>Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative + zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452</p> +<p>Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for + measurement error in analytical chemistry. Technometrics 37(2), 176-184.</p> + </div> + + <div class="section level2"> + <h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2> + <div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="co"># \dontrun{</span></span></span> +<span class="r-in"><span><span class="co"># The data have been generated using the following kinetic models</span></span></span> +<span class="r-in"><span><span class="va">m_synth_SFO_lin</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"SFO"</span>, to <span class="op">=</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="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"SFO"</span>, to <span class="op">=</span> <span class="st">"M2"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M2 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</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></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">m_synth_SFO_par</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"SFO"</span>, to <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">"M1"</span>, <span class="st">"M2"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M1 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M2 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</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></span> +<span class="r-in"><span><span class="va">m_synth_DFOP_lin</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"DFOP"</span>, to <span class="op">=</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="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"SFO"</span>, to <span class="op">=</span> <span class="st">"M2"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M2 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</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></span> +<span class="r-in"><span><span class="va">m_synth_DFOP_par</span> <span class="op"><-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></span><span class="op">(</span>type <span class="op">=</span> <span class="st">"DFOP"</span>, to <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">"M1"</span>, <span class="st">"M2"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> sink <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M1 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> M2 <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>type <span class="op">=</span> <span class="st">"SFO"</span><span class="op">)</span>, use_of_ff <span class="op">=</span> <span class="st">"max"</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></span> +<span class="r-in"><span><span class="co"># The model predictions without intentional error were generated as follows</span></span></span> +<span class="r-in"><span><span class="va">sampling_times</span> <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="fl">0</span>, <span class="fl">1</span>, <span class="fl">3</span>, <span class="fl">7</span>, <span class="fl">14</span>, <span class="fl">28</span>, <span class="fl">60</span>, <span class="fl">90</span>, <span class="fl">120</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">d_synth_SFO_lin</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k_parent <span class="op">=</span> <span class="fl">0.7</span>, f_parent_to_M1 <span class="op">=</span> <span class="fl">0.8</span>,</span></span> +<span class="r-in"><span> k_M1 <span class="op">=</span> <span class="fl">0.3</span>, f_M1_to_M2 <span class="op">=</span> <span class="fl">0.7</span>,</span></span> +<span class="r-in"><span> k_M2 <span class="op">=</span> <span class="fl">0.02</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, M1 <span class="op">=</span> <span class="fl">0</span>, M2 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">d_synth_DFOP_lin</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">m_synth_DFOP_lin</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="fl">0.2</span>, k2 <span class="op">=</span> <span class="fl">0.02</span>, g <span class="op">=</span> <span class="fl">0.5</span>,</span></span> +<span class="r-in"><span> f_parent_to_M1 <span class="op">=</span> <span class="fl">0.5</span>, k_M1 <span class="op">=</span> <span class="fl">0.3</span>,</span></span> +<span class="r-in"><span> f_M1_to_M2 <span class="op">=</span> <span class="fl">0.7</span>, k_M2 <span class="op">=</span> <span class="fl">0.02</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, M1 <span class="op">=</span> <span class="fl">0</span>, M2 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">d_synth_SFO_par</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">m_synth_SFO_par</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k_parent <span class="op">=</span> <span class="fl">0.2</span>,</span></span> +<span class="r-in"><span> f_parent_to_M1 <span class="op">=</span> <span class="fl">0.8</span>, k_M1 <span class="op">=</span> <span class="fl">0.01</span>,</span></span> +<span class="r-in"><span> f_parent_to_M2 <span class="op">=</span> <span class="fl">0.2</span>, k_M2 <span class="op">=</span> <span class="fl">0.02</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, M1 <span class="op">=</span> <span class="fl">0</span>, M2 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">d_synth_DFOP_par</span> <span class="op"><-</span> <span class="fu"><a href="mkinpredict.html">mkinpredict</a></span><span class="op">(</span><span class="va">m_synth_DFOP_par</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>k1 <span class="op">=</span> <span class="fl">0.3</span>, k2 <span class="op">=</span> <span class="fl">0.02</span>, g <span class="op">=</span> <span class="fl">0.7</span>,</span></span> +<span class="r-in"><span> f_parent_to_M1 <span class="op">=</span> <span class="fl">0.6</span>, k_M1 <span class="op">=</span> <span class="fl">0.04</span>,</span></span> +<span class="r-in"><span> f_parent_to_M2 <span class="op">=</span> <span class="fl">0.4</span>, k_M2 <span class="op">=</span> <span class="fl">0.01</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/c.html" class="external-link">c</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fl">100</span>, M1 <span class="op">=</span> <span class="fl">0</span>, M2 <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>,</span></span> +<span class="r-in"><span> <span class="va">sampling_times</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Construct names for datasets with errors</span></span></span> +<span class="r-in"><span><span class="va">d_synth_names</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="st">"d_synth_"</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">"SFO_lin"</span>, <span class="st">"SFO_par"</span>,</span></span> +<span class="r-in"><span> <span class="st">"DFOP_lin"</span>, <span class="st">"DFOP_par"</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Original function used or adding errors. The add_err function now published</span></span></span> +<span class="r-in"><span><span class="co"># with this package is a slightly generalised version where the names of</span></span></span> +<span class="r-in"><span><span class="co"># secondary compartments that should have an initial value of zero (M1 and M2</span></span></span> +<span class="r-in"><span><span class="co"># in this case) are not hardcoded any more.</span></span></span> +<span class="r-in"><span><span class="co"># add_err = function(d, sdfunc, LOD = 0.1, reps = 2, seed = 123456789)</span></span></span> +<span class="r-in"><span><span class="co"># {</span></span></span> +<span class="r-in"><span><span class="co"># set.seed(seed)</span></span></span> +<span class="r-in"><span><span class="co"># d_long = mkin_wide_to_long(d, time = "time")</span></span></span> +<span class="r-in"><span><span class="co"># d_rep = data.frame(lapply(d_long, rep, each = 2))</span></span></span> +<span class="r-in"><span><span class="co"># d_rep$value = rnorm(length(d_rep$value), d_rep$value, sdfunc(d_rep$value))</span></span></span> +<span class="r-in"><span><span class="co">#</span></span></span> +<span class="r-in"><span><span class="co"># d_rep[d_rep$time == 0 & d_rep$name %in% c("M1", "M2"), "value"] <- 0</span></span></span> +<span class="r-in"><span><span class="co"># d_NA <- transform(d_rep, value = ifelse(value < LOD, NA, value))</span></span></span> +<span class="r-in"><span><span class="co"># d_NA$value <- round(d_NA$value, 1)</span></span></span> +<span class="r-in"><span><span class="co"># return(d_NA)</span></span></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"># The following is the simplified version of the two-component model of Rocke</span></span></span> +<span class="r-in"><span><span class="co"># and Lorenzato (1995)</span></span></span> +<span class="r-in"><span><span class="va">sdfunc_twocomp</span> <span class="op">=</span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span>, <span class="va">sd_low</span>, <span class="va">rsd_high</span><span class="op">)</span> <span class="op">{</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/MathFun.html" class="external-link">sqrt</a></span><span class="op">(</span><span class="va">sd_low</span><span class="op">^</span><span class="fl">2</span> <span class="op">+</span> <span class="va">value</span><span class="op">^</span><span class="fl">2</span> <span class="op">*</span> <span class="va">rsd_high</span><span class="op">^</span><span class="fl">2</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># Add the errors.</span></span></span> +<span class="r-in"><span><span class="kw">for</span> <span class="op">(</span><span class="va">d_synth_name</span> <span class="kw">in</span> <span class="va">d_synth_names</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">{</span></span></span> +<span class="r-in"><span> <span class="va">d_synth</span> <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/get.html" class="external-link">get</a></span><span class="op">(</span><span class="va">d_synth_name</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/assign.html" class="external-link">assign</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="va">d_synth_name</span>, <span class="st">"_a"</span><span class="op">)</span>, <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">d_synth</span>, <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fl">3</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/assign.html" class="external-link">assign</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="va">d_synth_name</span>, <span class="st">"_b"</span><span class="op">)</span>, <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">d_synth</span>, <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fl">7</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/assign.html" class="external-link">assign</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste0</a></span><span class="op">(</span><span class="va">d_synth_name</span>, <span class="st">"_c"</span><span class="op">)</span>, <span class="fu"><a href="add_err.html">add_err</a></span><span class="op">(</span><span class="va">d_synth</span>,</span></span> +<span class="r-in"><span> <span class="kw">function</span><span class="op">(</span><span class="va">value</span><span class="op">)</span> <span class="fu">sdfunc_twocomp</span><span class="op">(</span><span class="va">value</span>, <span class="fl">0.5</span>, <span class="fl">0.07</span><span class="op">)</span><span class="op">)</span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="op">}</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="va">d_synth_err_names</span> <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></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/r/base/paste.html" class="external-link">paste</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/rep.html" class="external-link">rep</a></span><span class="op">(</span><span class="va">d_synth_names</span>, each <span class="op">=</span> <span class="fl">3</span><span class="op">)</span>, <span class="va">letters</span><span class="op">[</span><span class="fl">1</span><span class="op">:</span><span class="fl">3</span><span class="op">]</span>, sep <span class="op">=</span> <span class="st">"_"</span><span class="op">)</span></span></span> +<span class="r-in"><span><span class="op">)</span></span></span> +<span class="r-in"><span></span></span> +<span class="r-in"><span><span class="co"># This is just one example of an evaluation using the kinetic model used for</span></span></span> +<span class="r-in"><span><span class="co"># the generation of the data</span></span></span> +<span class="r-in"><span> <span class="va">fit</span> <span class="op"><-</span> <span class="fu"><a href="mkinfit.html">mkinfit</a></span><span class="op">(</span><span class="va">m_synth_SFO_lin</span>, <span class="va">synthetic_data_for_UBA_2014</span><span class="op">[[</span><span class="fl">1</span><span class="op">]</span><span class="op">]</span><span class="op">$</span><span class="va">data</span>,</span></span> +<span class="r-in"><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="synthetic_data_for_UBA_2014-1.png" alt="" width="700" height="433"></span> +<span class="r-in"><span> <span class="fu"><a href="https://rdrr.io/pkg/saemix/man/summary-methods.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: 1.2.10 </span> +<span class="r-out co"><span class="r-pr">#></span> R version used for fitting: 4.4.2 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of fit: Fri Feb 14 07:34:43 2025 </span> +<span class="r-out co"><span class="r-pr">#></span> Date of summary: Fri Feb 14 07:34:43 2025 </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 = - k_parent * parent</span> +<span class="r-out co"><span class="r-pr">#></span> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1</span> +<span class="r-out co"><span class="r-pr">#></span> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2</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 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 848 model solutions performed in 0.17 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> +<span class="r-out co"><span class="r-pr">#></span> Error model algorithm: OLS </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> +<span class="r-out co"><span class="r-pr">#></span> parent_0 101.3500 state</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.1000 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> k_M1 0.1001 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> k_M2 0.1002 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_M1 0.5000 deparm</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_to_M2 0.5000 deparm</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 the transformed parameters actually optimised:</span> +<span class="r-out co"><span class="r-pr">#></span> value lower upper</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 101.350000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -2.302585 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M1 -2.301586 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M2 -2.300587 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 0.000000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_qlogis 0.000000 -Inf Inf</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Fixed parameter values:</span> +<span class="r-out co"><span class="r-pr">#></span> value type</span> +<span class="r-out co"><span class="r-pr">#></span> M1_0 0 state</span> +<span class="r-out co"><span class="r-pr">#></span> M2_0 0 state</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Results:</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> AIC BIC logLik</span> +<span class="r-out co"><span class="r-pr">#></span> 188.7274 200.3723 -87.36368</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Optimised, transformed parameters with symmetric confidence intervals:</span> +<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_0 102.1000 1.57000 98.8600 105.3000</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent -0.3020 0.03885 -0.3812 -0.2229</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M1 -1.2070 0.07123 -1.3520 -1.0620</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M2 -3.9010 0.06571 -4.0350 -3.7670</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis 1.2010 0.23530 0.7216 1.6800</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_qlogis 0.9589 0.24890 0.4520 1.4660</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 2.2730 0.25740 1.7490 2.7970</span> +<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_parent log_k_M1 log_k_M2 f_parent_qlogis</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.000e+00 3.933e-01 -1.605e-01 2.819e-02 -4.624e-01</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent 3.933e-01 1.000e+00 -4.082e-01 7.166e-02 -5.682e-01</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M1 -1.605e-01 -4.082e-01 1.000e+00 -3.929e-01 7.478e-01</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M2 2.819e-02 7.166e-02 -3.929e-01 1.000e+00 -2.658e-01</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -4.624e-01 -5.682e-01 7.478e-01 -2.658e-01 1.000e+00</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_qlogis 1.614e-01 4.102e-01 -8.109e-01 5.419e-01 -8.605e-01</span> +<span class="r-out co"><span class="r-pr">#></span> sigma -1.377e-08 7.536e-10 1.089e-08 -4.422e-08 7.124e-09</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_qlogis sigma</span> +<span class="r-out co"><span class="r-pr">#></span> parent_0 1.614e-01 -1.377e-08</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_parent 4.102e-01 7.536e-10</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M1 -8.109e-01 1.089e-08</span> +<span class="r-out co"><span class="r-pr">#></span> log_k_M2 5.419e-01 -4.422e-08</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_qlogis -8.605e-01 7.124e-09</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_qlogis 1.000e+00 -2.685e-08</span> +<span class="r-out co"><span class="r-pr">#></span> sigma -2.685e-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> +<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_0 102.10000 65.000 7.281e-36 98.86000 105.30000</span> +<span class="r-out co"><span class="r-pr">#></span> k_parent 0.73930 25.740 2.948e-23 0.68310 0.80020</span> +<span class="r-out co"><span class="r-pr">#></span> k_M1 0.29920 14.040 1.577e-15 0.25880 0.34590</span> +<span class="r-out co"><span class="r-pr">#></span> k_M2 0.02023 15.220 1.653e-16 0.01769 0.02312</span> +<span class="r-out co"><span class="r-pr">#></span> f_parent_to_M1 0.76870 18.370 7.295e-19 0.67300 0.84290</span> +<span class="r-out co"><span class="r-pr">#></span> f_M1_to_M2 0.72290 14.500 6.418e-16 0.61110 0.81240</span> +<span class="r-out co"><span class="r-pr">#></span> sigma 2.27300 8.832 2.161e-10 1.74900 2.79700</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> FOCUS Chi2 error levels in percent:</span> +<span class="r-out co"><span class="r-pr">#></span> err.min n.optim df</span> +<span class="r-out co"><span class="r-pr">#></span> All data 8.454 6 17</span> +<span class="r-out co"><span class="r-pr">#></span> parent 8.660 2 6</span> +<span class="r-out co"><span class="r-pr">#></span> M1 10.583 2 5</span> +<span class="r-out co"><span class="r-pr">#></span> M2 3.586 2 6</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Resulting formation fractions:</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 0.7687</span> +<span class="r-out co"><span class="r-pr">#></span> parent_sink 0.2313</span> +<span class="r-out co"><span class="r-pr">#></span> M1_M2 0.7229</span> +<span class="r-out co"><span class="r-pr">#></span> M1_sink 0.2771</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Estimated disappearance times:</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 0.9376 3.114</span> +<span class="r-out co"><span class="r-pr">#></span> M1 2.3170 7.697</span> +<span class="r-out co"><span class="r-pr">#></span> M2 34.2689 113.839</span> +<span class="r-out co"><span class="r-pr">#></span> </span> +<span class="r-out co"><span class="r-pr">#></span> Data:</span> +<span class="r-out co"><span class="r-pr">#></span> time variable observed predicted residual</span> +<span class="r-out co"><span class="r-pr">#></span> 0 parent 101.5 1.021e+02 -0.56248</span> +<span class="r-out co"><span class="r-pr">#></span> 0 parent 101.2 1.021e+02 -0.86248</span> +<span class="r-out co"><span class="r-pr">#></span> 1 parent 53.9 4.873e+01 5.17118</span> +<span class="r-out co"><span class="r-pr">#></span> 1 parent 47.5 4.873e+01 -1.22882</span> +<span class="r-out co"><span class="r-pr">#></span> 3 parent 10.4 1.111e+01 -0.70773</span> +<span class="r-out co"><span class="r-pr">#></span> 3 parent 7.6 1.111e+01 -3.50773</span> +<span class="r-out co"><span class="r-pr">#></span> 7 parent 1.1 5.772e-01 0.52283</span> +<span class="r-out co"><span class="r-pr">#></span> 7 parent 0.3 5.772e-01 -0.27717</span> +<span class="r-out co"><span class="r-pr">#></span> 14 parent 3.5 3.264e-03 3.49674</span> +<span class="r-out co"><span class="r-pr">#></span> 28 parent 3.2 1.045e-07 3.20000</span> +<span class="r-out co"><span class="r-pr">#></span> 90 parent 0.6 9.532e-10 0.60000</span> +<span class="r-out co"><span class="r-pr">#></span> 120 parent 3.5 -5.940e-10 3.50000</span> +<span class="r-out co"><span class="r-pr">#></span> 1 M1 36.4 3.479e+01 1.61088</span> +<span class="r-out co"><span class="r-pr">#></span> 1 M1 37.4 3.479e+01 2.61088</span> +<span class="r-out co"><span class="r-pr">#></span> 3 M1 34.3 3.937e+01 -5.07027</span> +<span class="r-out co"><span class="r-pr">#></span> 3 M1 39.8 3.937e+01 0.42973</span> +<span class="r-out co"><span class="r-pr">#></span> 7 M1 15.1 1.549e+01 -0.38715</span> +<span class="r-out co"><span class="r-pr">#></span> 7 M1 17.8 1.549e+01 2.31285</span> +<span class="r-out co"><span class="r-pr">#></span> 14 M1 5.8 1.995e+00 3.80469</span> +<span class="r-out co"><span class="r-pr">#></span> 14 M1 1.2 1.995e+00 -0.79531</span> +<span class="r-out co"><span class="r-pr">#></span> 60 M1 0.5 2.111e-06 0.50000</span> +<span class="r-out co"><span class="r-pr">#></span> 90 M1 3.2 -9.672e-10 3.20000</span> +<span class="r-out co"><span class="r-pr">#></span> 120 M1 1.5 7.670e-10 1.50000</span> +<span class="r-out co"><span class="r-pr">#></span> 120 M1 0.6 7.670e-10 0.60000</span> +<span class="r-out co"><span class="r-pr">#></span> 1 M2 4.8 4.455e+00 0.34517</span> +<span class="r-out co"><span class="r-pr">#></span> 3 M2 20.9 2.153e+01 -0.62527</span> +<span class="r-out co"><span class="r-pr">#></span> 3 M2 19.3 2.153e+01 -2.22527</span> +<span class="r-out co"><span class="r-pr">#></span> 7 M2 42.0 4.192e+01 0.07941</span> +<span class="r-out co"><span class="r-pr">#></span> 7 M2 43.1 4.192e+01 1.17941</span> +<span class="r-out co"><span class="r-pr">#></span> 14 M2 49.4 4.557e+01 3.83353</span> +<span class="r-out co"><span class="r-pr">#></span> 14 M2 44.3 4.557e+01 -1.26647</span> +<span class="r-out co"><span class="r-pr">#></span> 28 M2 34.6 3.547e+01 -0.87275</span> +<span class="r-out co"><span class="r-pr">#></span> 28 M2 33.0 3.547e+01 -2.47275</span> +<span class="r-out co"><span class="r-pr">#></span> 60 M2 18.8 1.858e+01 0.21837</span> +<span class="r-out co"><span class="r-pr">#></span> 60 M2 17.6 1.858e+01 -0.98163</span> +<span class="r-out co"><span class="r-pr">#></span> 90 M2 10.6 1.013e+01 0.47130</span> +<span class="r-out co"><span class="r-pr">#></span> 90 M2 10.8 1.013e+01 0.67130</span> +<span class="r-out co"><span class="r-pr">#></span> 120 M2 9.8 5.521e+00 4.27893</span> +<span class="r-out co"><span class="r-pr">#></span> 120 M2 3.3 5.521e+00 -2.22107</span> +<span class="r-in"><span><span class="co"># }</span></span></span> +</code></pre></div> + </div> + </main><aside class="col-md-3"><nav id="toc" aria-label="Table of contents"><h2>On this page</h2> + </nav></aside></div> + + + <footer><div class="pkgdown-footer-left"> + <p>Developed by Johannes Ranke.</p> +</div> + +<div class="pkgdown-footer-right"> + <p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.1.1.</p> +</div> + + </footer></div> + + + + + + </body></html> + |