aboutsummaryrefslogtreecommitdiff
path: root/docs/reference/synthetic_data_for_UBA_2014.html
blob: 7fd2de8011ef0ac591a70dba9bda63256e8ac879 (plain) (blame)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
<!DOCTYPE html>
<!-- Generated by pkgdown: do not edit by hand --><html lang="en"><head><meta http-equiv="Content-Type" content="text/html; charset=UTF-8"><meta charset="utf-8"><meta http-equiv="X-UA-Compatible" content="IE=edge"><meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no"><meta name="description" content="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."><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-5.2.2/bootstrap.min.css" rel="stylesheet"><script src="../deps/bootstrap-5.2.2/bootstrap.bundle.min.js"></script><!-- Font Awesome icons --><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/all.min.css" integrity="sha256-mmgLkCYLUQbXn0B1SRqzHar6dCnv9oZFPEC1g1cwlkk=" crossorigin="anonymous"><link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/font-awesome/5.12.1/css/v4-shims.min.css" integrity="sha256-wZjR52fzng1pJHwx4aV2AO3yyTOXrcDW7jBpJtTwVxw=" crossorigin="anonymous"><!-- bootstrap-toc --><script src="https://cdn.jsdelivr.net/gh/afeld/bootstrap-toc@v1.0.1/dist/bootstrap-toc.min.js" integrity="sha256-4veVQbu7//Lk5TSmc7YV48MxtMy98e26cf5MrgZYnwo=" crossorigin="anonymous"></script><!-- headroom.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/headroom.min.js" integrity="sha256-AsUX4SJE1+yuDu5+mAVzJbuYNPHj/WroHuZ8Ir/CkE0=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/headroom/0.11.0/jQuery.headroom.min.js" integrity="sha256-ZX/yNShbjqsohH1k95liqY9Gd8uOiE1S4vZc+9KQ1K4=" crossorigin="anonymous"></script><!-- clipboard.js --><script src="https://cdnjs.cloudflare.com/ajax/libs/clipboard.js/2.0.6/clipboard.min.js" integrity="sha256-inc5kl9MA1hkeYUt+EC3BhlIgyp/2jDIyBLS6k3UxPI=" crossorigin="anonymous"></script><!-- search --><script src="https://cdnjs.cloudflare.com/ajax/libs/fuse.js/6.4.6/fuse.js" integrity="sha512-zv6Ywkjyktsohkbp9bb45V6tEMoWhzFzXis+LrMehmJZZSys19Yxf1dopHx7WzIKxr5tK2dVcYmaCk2uqdjF4A==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/autocomplete.js/0.38.0/autocomplete.jquery.min.js" integrity="sha512-GU9ayf+66Xx2TmpxqJpliWbT5PiGYxpaG8rfnBEk1LL8l1KGkRShhngwdXK1UgqhAzWpZHSiYPc09/NwDQIGyg==" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mark.js/8.11.1/mark.min.js" integrity="sha512-5CYOlHXGh6QpOFA/TeTylKLWfB3ftPsde7AnmhuitiTX4K5SqCLBeKro6sPS8ilsz1Q4NRx3v8Ko2IBiszzdww==" crossorigin="anonymous"></script><!-- pkgdown --><script src="../pkgdown.js"></script><meta property="og:title" content="Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014"><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."><!-- mathjax --><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js" integrity="sha256-nvJJv9wWKEm88qvoQl9ekL2J+k/RWIsaSScxxlsrv8k=" crossorigin="anonymous"></script><script src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/config/TeX-AMS-MML_HTMLorMML.js" integrity="sha256-84DKXVJXs0/F8OTMzX4UR909+jtl4G7SPypPavF+GfA=" crossorigin="anonymous"></script><!--[if lt IE 9]>
<script src="https://oss.maxcdn.com/html5shiv/3.7.3/html5shiv.min.js"></script>
<script src="https://oss.maxcdn.com/respond/1.4.2/respond.min.js"></script>
<![endif]--></head><body>
    <a href="#main" class="visually-hidden-focusable">Skip to contents</a>
    

    <nav class="navbar fixed-top navbar-default navbar-expand-lg bg-light"><div class="container">
    
    <a class="navbar-brand me-2" href="../index.html">mkin</a>

    <small class="nav-text text-default me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="Released version">1.2.6</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">
  <a href="#" class="nav-link dropdown-toggle" data-bs-toggle="dropdown" role="button" aria-expanded="false" aria-haspopup="true" id="dropdown-articles">Articles</a>
  <div class="dropdown-menu" aria-labelledby="dropdown-articles">
    <a class="dropdown-item" href="../articles/mkin.html">Introduction to mkin</a>
    <div class="dropdown-divider"></div>
    <h6 class="dropdown-header" data-toc-skip>Example evaluations with (generalised) nonlinear least squares</h6>
    <a class="dropdown-item" href="../articles/FOCUS_D.html">Example evaluation of FOCUS Example Dataset D</a>
    <a class="dropdown-item" href="../articles/FOCUS_L.html">Example evaluation of FOCUS Laboratory Data L1 to L3</a>
    <a class="dropdown-item" href="../articles/web_only/FOCUS_Z.html">Example evaluation of FOCUS Example Dataset Z</a>
    <div class="dropdown-divider"></div>
    <h6 class="dropdown-header" data-toc-skip>Example evaluations with hierarchical models (nonlinear mixed-effects models)</h6>
    <a class="dropdown-item" href="../articles/prebuilt/2022_dmta_parent.html">Testing hierarchical parent degradation kinetics with residue data on dimethenamid and dimethenamid-P</a>
    <a class="dropdown-item" href="../articles/prebuilt/2022_dmta_pathway.html">Testing hierarchical pathway kinetics with residue data on dimethenamid and dimethenamid-P</a>
    <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>
    <a class="dropdown-item" href="../articles/prebuilt/2022_cyan_pathway.html">Testing hierarchical pathway kinetics with residue data on cyantraniliprole</a>
    <a class="dropdown-item" href="../articles/web_only/dimethenamid_2018.html">Comparison of saemix and nlme evaluations of dimethenamid data from 2018</a>
    <a class="dropdown-item" href="../articles/web_only/multistart.html">Short demo of the multistart method</a>
    <div class="dropdown-divider"></div>
    <h6 class="dropdown-header" data-toc-skip>Performance</h6>
    <a class="dropdown-item" href="../articles/web_only/compiled_models.html">Performance benefit by using compiled model definitions in mkin</a>
    <a class="dropdown-item" href="../articles/web_only/benchmarks.html">Benchmark timings for mkin</a>
    <a class="dropdown-item" href="../articles/web_only/saem_benchmarks.html">Benchmark timings for saem.mmkin</a>
    <div class="dropdown-divider"></div>
    <h6 class="dropdown-header" data-toc-skip>Miscellaneous</h6>
    <a class="dropdown-item" href="../articles/twa.html">Calculation of time weighted average concentrations with mkin</a>
    <a class="dropdown-item" href="../articles/web_only/NAFTA_examples.html">Example evaluation of NAFTA SOP Attachment examples</a>
  </div>
</li>
<li class="nav-item">
  <a class="nav-link" href="../news/index.html">News</a>
</li>
      </ul><form class="form-inline my-2 my-lg-0" role="search">
        <input type="search" class="form-control me-sm-2" aria-label="Toggle navigation" name="search-input" data-search-index="../search.json" id="search-input" placeholder="Search for" autocomplete="off"></form>

      <ul class="navbar-nav"><li class="nav-item">
  <a class="external-link nav-link" href="https://github.com/jranke/mkin/" aria-label="github">
    <span class="fab 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">
      <img src="" class="logo" alt=""><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">&lt;-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="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">#&gt;</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">&lt;-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="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">#&gt;</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">&lt;-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="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">#&gt;</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">&lt;-</span> <span class="fu"><a href="mkinmod.html">mkinmod</a></span><span class="op">(</span>parent <span class="op">=</span> <span class="fu"><a href="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">#&gt;</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">&lt;-</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">&lt;-</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">&lt;-</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">&lt;-</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$time == 0 &amp; d_rep$name %in% c("M1", "M2"), "value"] &lt;- 0</span></span></span>
<span class="r-in"><span><span class="co">#   d_NA &lt;- transform(d_rep, value = ifelse(value &lt; LOD, NA, value))</span></span></span>
<span class="r-in"><span><span class="co">#   d_NA$value &lt;- round(d_NA$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">&lt;-</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">#&gt;</span> mkin version used for fitting:    1.2.6 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> R version used for fitting:       4.3.2 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Date of fit:     Thu Nov 16 04:20:07 2023 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Date of summary: Thu Nov 16 04:20:07 2023 </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Equations:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> d_parent/dt = - k_parent * parent</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Model predictions using solution type deSolve </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Fitted using 848 model solutions performed in 0.166 s</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Error model: Constant variance </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Error model algorithm: OLS </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Starting values for parameters to be optimised:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>                   value   type</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_0       101.3500  state</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_parent         0.1000 deparm</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_M1             0.1001 deparm</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_M2             0.1002 deparm</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_parent_to_M1   0.5000 deparm</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_M1_to_M2       0.5000 deparm</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Starting values for the transformed parameters actually optimised:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>                      value lower upper</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_0        101.350000  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_parent     -2.302585  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M1         -2.301586  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M2         -2.300587  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_parent_qlogis   0.000000  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_M1_qlogis       0.000000  -Inf   Inf</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Fixed parameter values:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>      value  type</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M1_0     0 state</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M2_0     0 state</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Results:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span>        AIC      BIC    logLik</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   188.7274 200.3723 -87.36368</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Optimised, transformed parameters with symmetric confidence intervals:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>                 Estimate Std. Error   Lower    Upper</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_0        102.1000    1.57000 98.8600 105.3000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_parent     -0.3020    0.03885 -0.3812  -0.2229</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M1         -1.2070    0.07123 -1.3520  -1.0620</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M2         -3.9010    0.06571 -4.0350  -3.7670</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_parent_qlogis   1.2010    0.23530  0.7216   1.6800</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_M1_qlogis       0.9589    0.24890  0.4520   1.4660</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> sigma             2.2730    0.25740  1.7490   2.7970</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Parameter correlation:</span>
<span class="r-out co"><span class="r-pr">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</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">#&gt;</span>                 f_M1_qlogis      sigma</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_0          1.614e-01 -1.377e-08</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_parent      4.102e-01  7.536e-10</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M1         -8.109e-01  1.089e-08</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> log_k_M2          5.419e-01 -4.422e-08</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_parent_qlogis  -8.605e-01  7.124e-09</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> f_M1_qlogis       1.000e+00 -2.685e-08</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> sigma            -2.685e-08  1.000e+00</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Backtransformed parameters:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Confidence intervals for internally transformed parameters are asymmetric.</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> t-test (unrealistically) based on the assumption of normal distribution</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> for estimators of untransformed parameters.</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>                 Estimate t value    Pr(&gt;t)    Lower     Upper</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_0       102.10000  65.000 7.281e-36 98.86000 105.30000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_parent         0.73930  25.740 2.948e-23  0.68310   0.80020</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_M1             0.29920  14.040 1.577e-15  0.25880   0.34590</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> k_M2             0.02023  15.220 1.653e-16  0.01769   0.02312</span>
<span class="r-out co"><span class="r-pr">#&gt;</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">#&gt;</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">#&gt;</span> sigma            2.27300   8.832 2.161e-10  1.74900   2.79700</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> FOCUS Chi2 error levels in percent:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>          err.min n.optim df</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> All data   8.454       6 17</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent     8.660       2  6</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M1        10.583       2  5</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M2         3.586       2  6</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Resulting formation fractions:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>                 ff</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_M1   0.7687</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent_sink 0.2313</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M1_M2       0.7229</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M1_sink     0.2771</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Estimated disappearance times:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>           DT50    DT90</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> parent  0.9376   3.114</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M1      2.3170   7.697</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> M2     34.2689 113.839</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> Data:</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>  time variable observed  predicted residual</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     0   parent    101.5  1.021e+02 -0.56248</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     0   parent    101.2  1.021e+02 -0.86248</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     1   parent     53.9  4.873e+01  5.17118</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     1   parent     47.5  4.873e+01 -1.22882</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3   parent     10.4  1.111e+01 -0.70773</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3   parent      7.6  1.111e+01 -3.50773</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7   parent      1.1  5.772e-01  0.52283</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7   parent      0.3  5.772e-01 -0.27717</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    14   parent      3.5  3.264e-03  3.49674</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    28   parent      3.2  1.045e-07  3.20000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    90   parent      0.6  9.532e-10  0.60000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   120   parent      3.5 -5.940e-10  3.50000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     1       M1     36.4  3.479e+01  1.61088</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     1       M1     37.4  3.479e+01  2.61088</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3       M1     34.3  3.937e+01 -5.07027</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3       M1     39.8  3.937e+01  0.42973</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7       M1     15.1  1.549e+01 -0.38715</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7       M1     17.8  1.549e+01  2.31285</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    14       M1      5.8  1.995e+00  3.80469</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    14       M1      1.2  1.995e+00 -0.79531</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    60       M1      0.5  2.111e-06  0.50000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    90       M1      3.2 -9.672e-10  3.20000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   120       M1      1.5  7.670e-10  1.50000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   120       M1      0.6  7.670e-10  0.60000</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     1       M2      4.8  4.455e+00  0.34517</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3       M2     20.9  2.153e+01 -0.62527</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     3       M2     19.3  2.153e+01 -2.22527</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7       M2     42.0  4.192e+01  0.07941</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>     7       M2     43.1  4.192e+01  1.17941</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    14       M2     49.4  4.557e+01  3.83353</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    14       M2     44.3  4.557e+01 -1.26647</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    28       M2     34.6  3.547e+01 -0.87275</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    28       M2     33.0  3.547e+01 -2.47275</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    60       M2     18.8  1.858e+01  0.21837</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    60       M2     17.6  1.858e+01 -0.98163</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    90       M2     10.6  1.013e+01  0.47130</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>    90       M2     10.8  1.013e+01  0.67130</span>
<span class="r-out co"><span class="r-pr">#&gt;</span>   120       M2      9.8  5.521e+00  4.27893</span>
<span class="r-out co"><span class="r-pr">#&gt;</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"><h2>On this page</h2>
    </nav></aside></div>


    <footer><div class="pkgdown-footer-left">
  <p></p><p>Developed by Johannes Ranke.</p>
</div>

<div class="pkgdown-footer-right">
  <p></p><p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.7.</p>
</div>

    </footer></div>

  

  

  </body></html>

Contact - Imprint