aboutsummaryrefslogtreecommitdiff
path: root/docs/reference/schaefer07_complex_case.html
blob: 9bb6d4eecb21cfd2bb454c3f315422e2e1cce176 (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
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
1001
1002
1003
1004
1005
1006
1007
1008
1009
1010
1011
1012
1013
1014
1015
1016
1017
1018
1019
1020
1021
1022
1023
1024
1025
1026
1027
1028
1029
1030
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
1050
1051
1052
1053
1054
1055
1056
1057
1058
1059
1060
1061
1062
1063
1064
1065
1066
1067
1068
1069
1070
1071
1072
1073
1074
1075
1076
1077
1078
1079
1080
1081
1082
1083
1084
1085
1086
1087
1088
1089
1090
1091
1092
1093
1094
1095
1096
1097
1098
1099
1100
1101
1102
1103
1104
1105
1106
1107
1108
1109
1110
1111
1112
1113
1114
1115
1116
1117
1118
1119
1120
1121
1122
1123
1124
1125
1126
1127
1128
1129
1130
1131
1132
1133
1134
1135
1136
1137
1138
1139
1140
1141
1142
1143
1144
1145
1146
1147
1148
1149
1150
1151
1152
1153
1154
1155
1156
1157
1158
1159
1160
1161
1162
1163
1164
1165
1166
1167
1168
1169
1170
1171
1172
1173
1174
1175
1176
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
<!-- Generated by pkgdown: do not edit by hand -->
<!DOCTYPE html>
<html>
  <head>
  <meta charset="utf-8">
<meta http-equiv="X-UA-Compatible" content="IE=edge">
<meta name="viewport" content="width=device-width, initial-scale=1.0">

<title>Metabolism data set used for checking the software quality of KinGUI — schaefer07_complex_case • mkin</title>

<!-- jquery -->
<script src="https://code.jquery.com/jquery-3.1.0.min.js" integrity="sha384-nrOSfDHtoPMzJHjVTdCopGqIqeYETSXhZDFyniQ8ZHcVy08QesyHcnOUpMpqnmWq" crossorigin="anonymous"></script>
<!-- Bootstrap -->

<link href="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-BVYiiSIFeK1dGmJRAkycuHAHRg32OmUcww7on3RYdg4Va+PmSTsz/K68vbdEjh4u" crossorigin="anonymous">
<script src="https://maxcdn.bootstrapcdn.com/bootstrap/3.3.7/js/bootstrap.min.js" integrity="sha384-Tc5IQib027qvyjSMfHjOMaLkfuWVxZxUPnCJA7l2mCWNIpG9mGCD8wGNIcPD7Txa" crossorigin="anonymous"></script>

<!-- Font Awesome icons -->
<link href="https://maxcdn.bootstrapcdn.com/font-awesome/4.6.3/css/font-awesome.min.css" rel="stylesheet" integrity="sha384-T8Gy5hrqNKT+hzMclPo118YTQO6cYprQmhrYwIiQ/3axmI1hQomh7Ud2hPOy8SP1" crossorigin="anonymous">


<!-- pkgdown -->
<link href="../pkgdown.css" rel="stylesheet">
<script src="../jquery.sticky-kit.min.js"></script>
<script src="../pkgdown.js"></script>

<!-- mathjax -->
<script src='https://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML'></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>
    <div class="container template-reference-topic">
      <header>
      <div class="navbar navbar-default navbar-fixed-top" role="navigation">
  <div class="container">
    <div class="navbar-header">
      <button type="button" class="navbar-toggle collapsed" data-toggle="collapse" data-target="#navbar">
        <span class="icon-bar"></span>
        <span class="icon-bar"></span>
        <span class="icon-bar"></span>
      </button>
      <a class="navbar-brand" href="../index.html">mkin</a>
    </div>
    <div id="navbar" class="navbar-collapse collapse">
      <ul class="nav navbar-nav">
        <li>
  <a href="../reference/index.html">Reference</a>
</li>
<li>
  <a href="../articles/index.html">Articles</a>
</li>
<li>
  <a href="../news/index.html">News</a>
</li>
      </ul>
      
      <ul class="nav navbar-nav navbar-right">
        <li>
  <a href="http://github.com/jranke/mkin">
    <span class="fa fa-github fa-lg"></span>
     
  </a>
</li>
      </ul>
    </div><!--/.nav-collapse -->
  </div><!--/.container -->
</div><!--/.navbar -->

      
      </header>

      <div class="row">
  <div class="col-md-9 contents">
    <div class="page-header">
    <h1>Metabolism data set used for checking the software quality of KinGUI</h1>
    </div>

    
    <p>This dataset was used for a comparison of KinGUI and ModelMaker to check the
  software quality of KinGUI in the original publication (Schäfer et al., 2007).
  The results from the fitting are also included.</p>
    

    <pre><span class='fu'>data</span>(<span class='no'>schaefer07_complex_case</span>)</pre>
        
    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>

    <p>The data set is a data frame with 8 observations on the following 6 variables.
  <dl class='dl-horizontal'>
    <dt><code>time</code></dt><dd>a numeric vector</dd>
    <dt><code>parent</code></dt><dd>a numeric vector</dd>
    <dt><code>A1</code></dt><dd>a numeric vector</dd>
    <dt><code>B1</code></dt><dd>a numeric vector</dd>
    <dt><code>C1</code></dt><dd>a numeric vector</dd>
    <dt><code>A2</code></dt><dd>a numeric vector</dd>
  </dl></p>
    <p>The results are a data frame with 14 results for different parameter values</p>
    
    <h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>

    <p>Schäfer D, Mikolasch B, Rainbird P and Harvey B (2007). KinGUI: a new kinetic
  software tool for evaluations according to FOCUS degradation kinetics. In: Del
  Re AAM, Capri E, Fragoulis G and Trevisan M (Eds.). Proceedings of the XIII
  Symposium Pesticide Chemistry, Piacenza, 2007, p. 916-923.</p>
    

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'><span class='no'>data</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkin_wide_to_long.html'>mkin_wide_to_long</a></span>(<span class='no'>schaefer07_complex_case</span>, <span class='kw'>time</span> <span class='kw'>=</span> <span class='st'>"time"</span>)
<span class='no'>model</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(
  <span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"A1"</span>, <span class='st'>"B1"</span>, <span class='st'>"C1"</span>), <span class='kw'>sink</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>),
  <span class='kw'>A1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"A2"</span>),
  <span class='kw'>B1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>),
  <span class='kw'>C1</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>),
  <span class='kw'>A2</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</span>), <span class='kw'>use_of_ff</span> <span class='kw'>=</span> <span class='st'>"max"</span>)</div><div class='output co'>#&gt; <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'><span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>model</span>, <span class='no'>data</span>)</div><div class='output co'>#&gt; Model cost at call  1 :  2511.655 
#&gt; Model cost at call  2 :  2511.655 
#&gt; Model cost at call  11 :  1436.639 
#&gt; Model cost at call  12 :  1436.638 
#&gt; Model cost at call  13 :  1436.566 
#&gt; Model cost at call  21 :  643.6583 
#&gt; Model cost at call  22 :  643.6583 
#&gt; Model cost at call  23 :  643.6582 
#&gt; Model cost at call  29 :  643.6576 
#&gt; Model cost at call  31 :  454.0244 
#&gt; Model cost at call  32 :  454.0241 
#&gt; Model cost at call  34 :  454.0229 
#&gt; Model cost at call  43 :  378.1144 
#&gt; Model cost at call  45 :  378.1143 
#&gt; Model cost at call  53 :  357.245 
#&gt; Model cost at call  55 :  357.2449 
#&gt; Model cost at call  56 :  357.2447 
#&gt; Model cost at call  63 :  354.3415 
#&gt; Model cost at call  64 :  354.3415 
#&gt; Model cost at call  65 :  354.3413 
#&gt; Model cost at call  73 :  332.49 
#&gt; Model cost at call  74 :  332.49 
#&gt; Model cost at call  81 :  332.4899 
#&gt; Model cost at call  83 :  315.2962 
#&gt; Model cost at call  84 :  306.3085 
#&gt; Model cost at call  86 :  306.3084 
#&gt; Model cost at call  87 :  306.3084 
#&gt; Model cost at call  92 :  306.3083 
#&gt; Model cost at call  94 :  290.6377 
#&gt; Model cost at call  96 :  290.6375 
#&gt; Model cost at call  98 :  290.6375 
#&gt; Model cost at call  101 :  290.6371 
#&gt; Model cost at call  105 :  269.09 
#&gt; Model cost at call  107 :  269.0899 
#&gt; Model cost at call  115 :  259.7551 
#&gt; Model cost at call  120 :  259.7549 
#&gt; Model cost at call  123 :  259.7547 
#&gt; Model cost at call  126 :  253.7973 
#&gt; Model cost at call  128 :  253.7972 
#&gt; Model cost at call  137 :  251.7358 
#&gt; Model cost at call  139 :  251.7358 
#&gt; Model cost at call  147 :  250.7394 
#&gt; Model cost at call  149 :  250.7393 
#&gt; Model cost at call  157 :  249.1148 
#&gt; Model cost at call  159 :  249.1148 
#&gt; Model cost at call  167 :  246.8768 
#&gt; Model cost at call  169 :  246.8768 
#&gt; Model cost at call  177 :  244.9758 
#&gt; Model cost at call  179 :  244.9758 
#&gt; Model cost at call  187 :  243.2914 
#&gt; Model cost at call  189 :  243.2914 
#&gt; Model cost at call  190 :  243.2914 
#&gt; Model cost at call  194 :  243.2914 
#&gt; Model cost at call  199 :  242.9202 
#&gt; Model cost at call  201 :  242.9202 
#&gt; Model cost at call  202 :  242.9202 
#&gt; Model cost at call  209 :  242.7695 
#&gt; Model cost at call  211 :  242.7695 
#&gt; Model cost at call  216 :  242.7695 
#&gt; Model cost at call  219 :  242.5771 
#&gt; Model cost at call  221 :  242.5771 
#&gt; Model cost at call  229 :  242.4402 
#&gt; Model cost at call  231 :  242.4402 
#&gt; Model cost at call  239 :  242.1878 
#&gt; Model cost at call  241 :  242.1878 
#&gt; Model cost at call  249 :  242.0553 
#&gt; Model cost at call  251 :  242.0553 
#&gt; Model cost at call  256 :  242.0553 
#&gt; Model cost at call  259 :  241.8761 
#&gt; Model cost at call  260 :  241.7412 
#&gt; Model cost at call  261 :  241.6954 
#&gt; Model cost at call  264 :  241.6954 
#&gt; Model cost at call  275 :  241.5982 
#&gt; Model cost at call  277 :  241.5982 
#&gt; Model cost at call  285 :  241.5459 
#&gt; Model cost at call  287 :  241.5459 
#&gt; Model cost at call  295 :  241.4837 
#&gt; Model cost at call  297 :  241.4837 
#&gt; Model cost at call  305 :  241.3882 
#&gt; Model cost at call  306 :  241.3161 
#&gt; Model cost at call  307 :  241.2315 
#&gt; Model cost at call  309 :  241.2315 
#&gt; Model cost at call  314 :  241.2315 
#&gt; Model cost at call  317 :  240.9738 
#&gt; Model cost at call  322 :  240.9738 
#&gt; Model cost at call  327 :  240.8244 
#&gt; Model cost at call  329 :  240.8244 
#&gt; Model cost at call  337 :  240.7005 
#&gt; Model cost at call  339 :  240.7005 
#&gt; Model cost at call  342 :  240.7005 
#&gt; Model cost at call  347 :  240.629 
#&gt; Model cost at call  350 :  240.629 
#&gt; Model cost at call  357 :  240.6193 
#&gt; Model cost at call  358 :  240.6193 
#&gt; Model cost at call  364 :  240.6193 
#&gt; Model cost at call  367 :  240.6193 
#&gt; Model cost at call  369 :  240.5873 
#&gt; Model cost at call  374 :  240.5873 
#&gt; Model cost at call  380 :  240.578 
#&gt; Model cost at call  382 :  240.578 
#&gt; Model cost at call  390 :  240.5723 
#&gt; Model cost at call  393 :  240.5723 
#&gt; Model cost at call  403 :  240.569 
#&gt; Model cost at call  404 :  240.569 
#&gt; Model cost at call  413 :  240.569 
#&gt; Model cost at call  415 :  240.5688 
#&gt; Model cost at call  416 :  240.5688 
#&gt; Model cost at call  417 :  240.5688 
#&gt; Model cost at call  431 :  240.5686 
#&gt; Model cost at call  432 :  240.5686 
#&gt; Model cost at call  434 :  240.5686 
#&gt; Model cost at call  443 :  240.5686 
#&gt; Model cost at call  444 :  240.5686 
#&gt; Model cost at call  447 :  240.5686 
#&gt; Model cost at call  449 :  240.5686 
#&gt; Model cost at call  450 :  240.5686 
#&gt; Model cost at call  466 :  240.5686 
#&gt; Model cost at call  470 :  240.5686 
#&gt; Model cost at call  485 :  240.5686 
#&gt; Model cost at call  509 :  240.5686 
#&gt; Optimisation by method Port successfully terminated.</div><div class='output co'>#&gt; $par
#&gt;       parent_0   log_k_parent       log_k_A1       log_k_B1       log_k_C1 
#&gt;     91.9181598     -3.0020485     -4.2735924     -3.9846764     -2.7852180 
#&gt;       log_k_A2 f_parent_ilr_1 f_parent_ilr_2     f_A1_ilr_1 
#&gt;     -3.7166415      0.4718588     -0.3589948     -0.1477244 
#&gt; 
#&gt; $ssr
#&gt; [1] 240.5686
#&gt; 
#&gt; $convergence
#&gt; [1] 0
#&gt; 
#&gt; $iterations
#&gt; [1] 43
#&gt; 
#&gt; $evaluations
#&gt; function gradient 
#&gt;       62      441 
#&gt; 
#&gt; $counts
#&gt; [1] &quot;relative convergence (4)&quot;
#&gt; 
#&gt; $hessian
#&gt;                   parent_0 log_k_parent      log_k_A1      log_k_B1
#&gt; parent_0         7.3650812   -92.141920 -1.001134e+01 -2.432415e+00
#&gt; log_k_parent   -92.1419204  6632.673492 -4.316240e+01 -1.320833e+01
#&gt; log_k_A1       -10.0113364   -43.162398  6.071628e+02  0.000000e+00
#&gt; log_k_B1        -2.4324147   -13.208329  0.000000e+00  1.572303e+02
#&gt; log_k_C1        -4.7153201  -118.288037 -5.878291e-05 -3.073041e-06
#&gt; log_k_A2        -0.4360727    -5.304259 -1.977980e+01  0.000000e+00
#&gt; f_parent_ilr_1  10.5460899   271.145438 -5.299954e+02  1.874235e+02
#&gt; f_parent_ilr_2  11.6409409   222.570696 -4.773816e+02 -1.159875e+02
#&gt; f_A1_ilr_1       0.5572072    10.374810  2.850173e+01  0.000000e+00
#&gt;                     log_k_C1      log_k_A2 f_parent_ilr_1 f_parent_ilr_2
#&gt; parent_0       -4.715320e+00 -4.360727e-01       10.54609       11.64094
#&gt; log_k_parent   -1.182880e+02 -5.304259e+00      271.14544      222.57070
#&gt; log_k_A1       -5.878291e-05 -1.977980e+01     -529.99537     -477.38164
#&gt; log_k_B1       -3.073041e-06  0.000000e+00      187.42348     -115.98754
#&gt; log_k_C1        3.372749e+02 -2.395674e-06       56.85184      305.98862
#&gt; log_k_A2       -2.395674e-06  2.749192e+01      -23.08549      -20.79373
#&gt; f_parent_ilr_1  5.685184e+01 -2.308549e+01     1256.24941      632.09769
#&gt; f_parent_ilr_2  3.059886e+02 -2.079373e+01      632.09769     1250.65147
#&gt; f_A1_ilr_1      3.158891e-06 -3.129286e+01       29.49830       26.56991
#&gt;                   f_A1_ilr_1
#&gt; parent_0        5.572072e-01
#&gt; log_k_parent    1.037481e+01
#&gt; log_k_A1        2.850173e+01
#&gt; log_k_B1        0.000000e+00
#&gt; log_k_C1        3.158891e-06
#&gt; log_k_A2       -3.129286e+01
#&gt; f_parent_ilr_1  2.949830e+01
#&gt; f_parent_ilr_2  2.656991e+01
#&gt; f_A1_ilr_1      3.998554e+01
#&gt; 
#&gt; $residuals
#&gt;     parent     parent     parent     parent     parent     parent     parent 
#&gt; -1.2818402 -1.9372115 -0.5105519  3.8165318 -2.3531716  4.8043342 -2.2775432 
#&gt;     parent         A1         A1         A1         A1         A1         A1 
#&gt; -5.3608524  4.1967522  2.9032987 -1.3124875 -0.6021093  2.5092324 -1.8861396 
#&gt;         B1         B1         B1         B1         B1         C1         C1 
#&gt;  4.3801768  5.5002481 -5.7917184  1.3852658  0.5313301  1.2796458  1.7105311 
#&gt;         C1         C1         C1         C1         C1         A2         A2 
#&gt;  3.7116712 -0.1182953  0.5228429 -0.8570298 -3.5476556 -0.5447276 -1.3652404 
#&gt;         A2         A2         A2         A2         A2 
#&gt; -0.3330261 -0.5802059  0.1285850  0.2119280 -0.1381990 
#&gt; 
#&gt; $ms
#&gt; [1] 7.289956
#&gt; 
#&gt; $var_ms
#&gt;     parent         A1         B1         C1         A2 
#&gt; 10.3459333  6.3301336 17.0367907  4.5639474  0.3841002 
#&gt; 
#&gt; $var_ms_unscaled
#&gt;     parent         A1         B1         C1         A2 
#&gt; 10.3459333  6.3301336 17.0367907  4.5639474  0.3841002 
#&gt; 
#&gt; $var_ms_unweighted
#&gt;     parent         A1         B1         C1         A2 
#&gt; 10.3459333  6.3301336 17.0367907  4.5639474  0.3841002 
#&gt; 
#&gt; $rank
#&gt; [1] 9
#&gt; 
#&gt; $df.residual
#&gt; [1] 24
#&gt; 
#&gt; $solution_type
#&gt; [1] &quot;deSolve&quot;
#&gt; 
#&gt; $transform_rates
#&gt; [1] TRUE
#&gt; 
#&gt; $transform_fractions
#&gt; [1] TRUE
#&gt; 
#&gt; $method.modFit
#&gt; [1] &quot;Port&quot;
#&gt; 
#&gt; $maxit.modFit
#&gt; [1] &quot;auto&quot;
#&gt; 
#&gt; $calls
#&gt; [1] 523
#&gt; 
#&gt; $time
#&gt;    user  system elapsed 
#&gt;   5.004   0.000   5.004 
#&gt; 
#&gt; $mkinmod
#&gt; &lt;mkinmod&gt; model generated with
#&gt; Use of formation fractions $use_of_ff: max 
#&gt; Specification $spec:
#&gt; $parent
#&gt; $type: SFO; $to: A1, B1, C1; $sink: FALSE
#&gt; $A1
#&gt; $type: SFO; $to: A2; $sink: TRUE
#&gt; $B1
#&gt; $type: SFO; $sink: TRUE
#&gt; $C1
#&gt; $type: SFO; $sink: TRUE
#&gt; $A2
#&gt; $type: SFO; $sink: TRUE
#&gt; Coefficient matrix $coefmat available
#&gt; Compiled model $cf available
#&gt; 
#&gt; $observed
#&gt;      name time value
#&gt; 1  parent    0 93.20
#&gt; 2  parent    1 89.40
#&gt; 3  parent    3 79.70
#&gt; 4  parent    7 61.10
#&gt; 5  parent   14 48.20
#&gt; 6  parent   30 15.90
#&gt; 7  parent   62  6.50
#&gt; 8  parent  100  6.00
#&gt; 9      A1    0    NA
#&gt; 10     A1    1    NA
#&gt; 11     A1    3  0.55
#&gt; 12     A1    7  6.87
#&gt; 13     A1   14 17.08
#&gt; 14     A1   30 21.68
#&gt; 15     A1   62 15.77
#&gt; 16     A1  100 13.63
#&gt; 17     B1    0    NA
#&gt; 18     B1    1    NA
#&gt; 19     B1    3    NA
#&gt; 20     B1    7  0.55
#&gt; 21     B1   14  2.31
#&gt; 22     B1   30 15.76
#&gt; 23     B1   62  6.36
#&gt; 24     B1  100  3.74
#&gt; 25     C1    0    NA
#&gt; 26     C1    1  0.55
#&gt; 27     C1    3  3.20
#&gt; 28     C1    7  5.46
#&gt; 29     C1   14 12.55
#&gt; 30     C1   30 10.45
#&gt; 31     C1   62  4.74
#&gt; 32     C1  100  4.33
#&gt; 33     A2    0    NA
#&gt; 34     A2    1  0.55
#&gt; 35     A2    3  1.41
#&gt; 36     A2    7  0.55
#&gt; 37     A2   14  1.29
#&gt; 38     A2   30  1.95
#&gt; 39     A2   62  3.54
#&gt; 40     A2  100  3.86
#&gt; 
#&gt; $obs_vars
#&gt; [1] &quot;parent&quot; &quot;A1&quot;     &quot;B1&quot;     &quot;C1&quot;     &quot;A2&quot;    
#&gt; 
#&gt; $predicted
#&gt;       name       time        value
#&gt; 1   parent   0.000000 91.918159794
#&gt; 2   parent   1.000000 87.462788491
#&gt; 3   parent   1.010101 87.418904506
#&gt; 4   parent   2.020202 83.139880984
#&gt; 5   parent   3.000000 79.189448055
#&gt; 6   parent   3.030303 79.070309209
#&gt; 7   parent   4.040404 75.199936833
#&gt; 8   parent   5.050505 71.519013349
#&gt; 9   parent   6.060606 68.018265517
#&gt; 10  parent   7.000000 64.916531757
#&gt; 11  parent   7.070707 64.688874011
#&gt; 12  parent   8.080808 61.522451197
#&gt; 13  parent   9.090909 58.511020005
#&gt; 14  parent  10.101010 55.646993828
#&gt; 15  parent  11.111111 52.923157412
#&gt; 16  parent  12.121212 50.332648680
#&gt; 17  parent  13.131313 47.868941444
#&gt; 18  parent  14.000000 45.846828365
#&gt; 19  parent  14.141414 45.525828960
#&gt; 20  parent  15.151515 43.297408299
#&gt; 21  parent  16.161616 41.178065468
#&gt; 22  parent  17.171717 39.162461272
#&gt; 23  parent  18.181818 37.245517861
#&gt; 24  parent  19.191919 35.422405939
#&gt; 25  parent  20.202020 33.688532595
#&gt; 26  parent  21.212121 32.039529737
#&gt; 27  parent  22.222222 30.471243081
#&gt; 28  parent  23.232323 28.979721692
#&gt; 29  parent  24.242424 27.561208025
#&gt; 30  parent  25.252525 26.212128463
#&gt; 31  parent  26.262626 24.929084310
#&gt; 32  parent  27.272727 23.708843233
#&gt; 33  parent  28.282828 22.548331117
#&gt; 34  parent  29.292929 21.444624318
#&gt; 35  parent  30.000000 20.704334210
#&gt; 36  parent  30.303030 20.394942302
#&gt; 37  parent  31.313131 19.396640638
#&gt; 38  parent  32.323232 18.447204335
#&gt; 39  parent  33.333333 17.544241506
#&gt; 40  parent  34.343434 16.685477346
#&gt; 41  parent  35.353535 15.868748397
#&gt; 42  parent  36.363636 15.091997098
#&gt; 43  parent  37.373737 14.353266603
#&gt; 44  parent  38.383838 13.650695852
#&gt; 45  parent  39.393939 12.982514879
#&gt; 46  parent  40.404040 12.347040357
#&gt; 47  parent  41.414141 11.742671354
#&gt; 48  parent  42.424242 11.167885303
#&gt; 49  parent  43.434343 10.621234162
#&gt; 50  parent  44.444444 10.101340770
#&gt; 51  parent  45.454545  9.606895375
#&gt; 52  parent  46.464646  9.136652336
#&gt; 53  parent  47.474747  8.689426985
#&gt; 54  parent  48.484848  8.264092640
#&gt; 55  parent  49.494949  7.859577770
#&gt; 56  parent  50.505051  7.474863293
#&gt; 57  parent  51.515152  7.108980009
#&gt; 58  parent  52.525253  6.761006160
#&gt; 59  parent  53.535354  6.430065106
#&gt; 60  parent  54.545455  6.115323117
#&gt; 61  parent  55.555556  5.815987274
#&gt; 62  parent  56.565657  5.531303470
#&gt; 63  parent  57.575758  5.260554508
#&gt; 64  parent  58.585859  5.003058299
#&gt; 65  parent  59.595960  4.758166141
#&gt; 66  parent  60.606061  4.525261085
#&gt; 67  parent  61.616162  4.303756381
#&gt; 68  parent  62.000000  4.222456793
#&gt; 69  parent  62.626263  4.093093997
#&gt; 70  parent  63.636364  3.892743220
#&gt; 71  parent  64.646465  3.702199310
#&gt; 72  parent  65.656566  3.520982238
#&gt; 73  parent  66.666667  3.348635468
#&gt; 74  parent  67.676768  3.184724813
#&gt; 75  parent  68.686869  3.028837337
#&gt; 76  parent  69.696970  2.880580317
#&gt; 77  parent  70.707071  2.739580256
#&gt; 78  parent  71.717172  2.605481934
#&gt; 79  parent  72.727273  2.477947523
#&gt; 80  parent  73.737374  2.356655730
#&gt; 81  parent  74.747475  2.241300986
#&gt; 82  parent  75.757576  2.131592683
#&gt; 83  parent  76.767677  2.027254437
#&gt; 84  parent  77.777778  1.928023390
#&gt; 85  parent  78.787879  1.833649553
#&gt; 86  parent  79.797980  1.743895173
#&gt; 87  parent  80.808081  1.658534134
#&gt; 88  parent  81.818182  1.577351390
#&gt; 89  parent  82.828283  1.500142419
#&gt; 90  parent  83.838384  1.426712710
#&gt; 91  parent  84.848485  1.356877275
#&gt; 92  parent  85.858586  1.290460179
#&gt; 93  parent  86.868687  1.227294099
#&gt; 94  parent  87.878788  1.167219904
#&gt; 95  parent  88.888889  1.110086250
#&gt; 96  parent  89.898990  1.055749203
#&gt; 97  parent  90.909091  1.004071872
#&gt; 98  parent  91.919192  0.954924068
#&gt; 99  parent  92.929293  0.908181975
#&gt; 100 parent  93.939394  0.863727837
#&gt; 101 parent  94.949495  0.821449662
#&gt; 102 parent  95.959596  0.781240940
#&gt; 103 parent  96.969697  0.743000375
#&gt; 104 parent  97.979798  0.706631627
#&gt; 105 parent  98.989899  0.672043075
#&gt; 106 parent 100.000000  0.639147580
#&gt; 107     A1   0.000000  0.000000000
#&gt; 108     A1   1.000000  1.685461006
#&gt; 109     A1   1.010101  1.701940789
#&gt; 110     A1   2.020202  3.296791533
#&gt; 111     A1   3.000000  4.746752202
#&gt; 112     A1   3.030303  4.790126465
#&gt; 113     A1   4.040404  6.187242320
#&gt; 114     A1   5.050505  7.493171988
#&gt; 115     A1   6.060606  8.712697491
#&gt; 116     A1   7.000000  9.773298725
#&gt; 117     A1   7.070707  9.850362326
#&gt; 118     A1   8.080808 10.910483202
#&gt; 119     A1   9.090909 11.897161206
#&gt; 120     A1  10.101010 12.814292412
#&gt; 121     A1  11.111111 13.665577981
#&gt; 122     A1  12.121212 14.454533757
#&gt; 123     A1  13.131313 15.184499397
#&gt; 124     A1  14.000000 15.767512526
#&gt; 125     A1  14.141414 15.858647054
#&gt; 126     A1  15.151515 16.479989628
#&gt; 127     A1  16.161616 17.051388624
#&gt; 128     A1  17.171717 17.575561608
#&gt; 129     A1  18.181818 18.055089316
#&gt; 130     A1  19.191919 18.492422399
#&gt; 131     A1  20.202020 18.889887843
#&gt; 132     A1  21.212121 19.249695079
#&gt; 133     A1  22.222222 19.573941783
#&gt; 134     A1  23.232323 19.864619397
#&gt; 135     A1  24.242424 20.123618383
#&gt; 136     A1  25.252525 20.352733211
#&gt; 137     A1  26.262626 20.553667106
#&gt; 138     A1  27.272727 20.728036563
#&gt; 139     A1  28.282828 20.877375640
#&gt; 140     A1  29.292929 21.003140039
#&gt; 141     A1  30.000000 21.077890710
#&gt; 142     A1  30.303030 21.106710984
#&gt; 143     A1  31.313131 21.189398917
#&gt; 144     A1  32.323232 21.252447002
#&gt; 145     A1  33.333333 21.297034466
#&gt; 146     A1  34.343434 21.324279770
#&gt; 147     A1  35.353535 21.335243623
#&gt; 148     A1  36.363636 21.330931858
#&gt; 149     A1  37.373737 21.312298151
#&gt; 150     A1  38.383838 21.280246621
#&gt; 151     A1  39.393939 21.235634295
#&gt; 152     A1  40.404040 21.179273450
#&gt; 153     A1  41.414141 21.111933845
#&gt; 154     A1  42.424242 21.034344838
#&gt; 155     A1  43.434343 20.947197407
#&gt; 156     A1  44.444444 20.851146060
#&gt; 157     A1  45.454545 20.746810660
#&gt; 158     A1  46.464646 20.634778158
#&gt; 159     A1  47.474747 20.515604239
#&gt; 160     A1  48.484848 20.389814887
#&gt; 161     A1  49.494949 20.257907875
#&gt; 162     A1  50.505051 20.120354180
#&gt; 163     A1  51.515152 19.977599327
#&gt; 164     A1  52.525253 19.830064674
#&gt; 165     A1  53.535354 19.678148618
#&gt; 166     A1  54.545455 19.522227762
#&gt; 167     A1  55.555556 19.362658007
#&gt; 168     A1  56.565657 19.199775600
#&gt; 169     A1  57.575758 19.033898126
#&gt; 170     A1  58.585859 18.865325451
#&gt; 171     A1  59.595960 18.694340625
#&gt; 172     A1  60.606061 18.521210729
#&gt; 173     A1  61.616162 18.346187688
#&gt; 174     A1  62.000000 18.279232408
#&gt; 175     A1  62.626263 18.169509043
#&gt; 176     A1  63.636364 17.991398686
#&gt; 177     A1  64.646465 17.812067549
#&gt; 178     A1  65.656566 17.631714275
#&gt; 179     A1  66.666667 17.450525840
#&gt; 180     A1  67.676768 17.268678156
#&gt; 181     A1  68.686869 17.086336636
#&gt; 182     A1  69.696970 16.903656738
#&gt; 183     A1  70.707071 16.720784474
#&gt; 184     A1  71.717172 16.537856901
#&gt; 185     A1  72.727273 16.355002582
#&gt; 186     A1  73.737374 16.172342031
#&gt; 187     A1  74.747475 15.989988127
#&gt; 188     A1  75.757576 15.808046514
#&gt; 189     A1  76.767677 15.626615980
#&gt; 190     A1  77.777778 15.445788814
#&gt; 191     A1  78.787879 15.265651148
#&gt; 192     A1  79.797980 15.086283284
#&gt; 193     A1  80.808081 14.907759996
#&gt; 194     A1  81.818182 14.730150830
#&gt; 195     A1  82.828283 14.553520376
#&gt; 196     A1  83.838384 14.377928535
#&gt; 197     A1  84.848485 14.203430771
#&gt; 198     A1  85.858586 14.030078345
#&gt; 199     A1  86.868687 13.857918547
#&gt; 200     A1  87.878788 13.686994907
#&gt; 201     A1  88.888889 13.517347398
#&gt; 202     A1  89.898990 13.349012635
#&gt; 203     A1  90.909091 13.182024056
#&gt; 204     A1  91.919192 13.016412097
#&gt; 205     A1  92.929293 12.852204356
#&gt; 206     A1  93.939394 12.689425755
#&gt; 207     A1  94.949495 12.528098688
#&gt; 208     A1  95.959596 12.368243159
#&gt; 209     A1  96.969697 12.209876925
#&gt; 210     A1  97.979798 12.053015616
#&gt; 211     A1  98.989899 11.897672861
#&gt; 212     A1 100.000000 11.743860400
#&gt; 213     B1   0.000000  0.000000000
#&gt; 214     B1   1.000000  0.862762059
#&gt; 215     B1   1.010101  0.871177048
#&gt; 216     B1   2.020202  1.683497848
#&gt; 217     B1   3.000000  2.418226457
#&gt; 218     B1   3.030303  2.440145075
#&gt; 219     B1   4.040404  3.144139999
#&gt; 220     B1   5.050505  3.798350490
#&gt; 221     B1   6.060606  4.405498633
#&gt; 222     B1   7.000000  4.930176837
#&gt; 223     B1   7.070707  4.968167964
#&gt; 224     B1   8.080808  5.488810347
#&gt; 225     B1   9.090909  5.969752521
#&gt; 226     B1  10.101010  6.413202316
#&gt; 227     B1  11.111111  6.821254568
#&gt; 228     B1  12.121212  7.195896744
#&gt; 229     B1  13.131313  7.539014282
#&gt; 230     B1  14.000000  7.810248132
#&gt; 231     B1  14.141414  7.852395679
#&gt; 232     B1  15.151515  8.137737320
#&gt; 233     B1  16.161616  8.396648072
#&gt; 234     B1  17.171717  8.630653651
#&gt; 235     B1  18.181818  8.841200774
#&gt; 236     B1  19.191919  9.029661109
#&gt; 237     B1  20.202020  9.197335022
#&gt; 238     B1  21.212121  9.345455150
#&gt; 239     B1  22.222222  9.475189788
#&gt; 240     B1  23.232323  9.587646116
#&gt; 241     B1  24.242424  9.683873262
#&gt; 242     B1  25.252525  9.764865214
#&gt; 243     B1  26.262626  9.831563593
#&gt; 244     B1  27.272727  9.884860284
#&gt; 245     B1  28.282828  9.925599936
#&gt; 246     B1  29.292929  9.954582344
#&gt; 247     B1  30.000000  9.968281596
#&gt; 248     B1  30.303030  9.972564708
#&gt; 249     B1  31.313131  9.980263783
#&gt; 250     B1  32.323232  9.978357919
#&gt; 251     B1  33.333333  9.967489009
#&gt; 252     B1  34.343434  9.948264327
#&gt; 253     B1  35.353535  9.921258285
#&gt; 254     B1  36.363636  9.887014102
#&gt; 255     B1  37.373737  9.846045383
#&gt; 256     B1  38.383838  9.798837632
#&gt; 257     B1  39.393939  9.745849674
#&gt; 258     B1  40.404040  9.687515023
#&gt; 259     B1  41.414141  9.624243169
#&gt; 260     B1  42.424242  9.556420809
#&gt; 261     B1  43.434343  9.484413012
#&gt; 262     B1  44.444444  9.408564328
#&gt; 263     B1  45.454545  9.329199843
#&gt; 264     B1  46.464646  9.246626179
#&gt; 265     B1  47.474747  9.161132446
#&gt; 266     B1  48.484848  9.072991146
#&gt; 267     B1  49.494949  8.982459028
#&gt; 268     B1  50.505051  8.889777910
#&gt; 269     B1  51.515152  8.795175451
#&gt; 270     B1  52.525253  8.698865886
#&gt; 271     B1  53.535354  8.601050726
#&gt; 272     B1  54.545455  8.501919425
#&gt; 273     B1  55.555556  8.401650008
#&gt; 274     B1  56.565657  8.300409672
#&gt; 275     B1  57.575758  8.198355355
#&gt; 276     B1  58.585859  8.095634277
#&gt; 277     B1  59.595960  7.992384454
#&gt; 278     B1  60.606061  7.888735183
#&gt; 279     B1  61.616162  7.784807509
#&gt; 280     B1  62.000000  7.745265792
#&gt; 281     B1  62.626263  7.680714664
#&gt; 282     B1  63.636364  7.576562482
#&gt; 283     B1  64.646465  7.472449799
#&gt; 284     B1  65.656566  7.368468826
#&gt; 285     B1  66.666667  7.264705509
#&gt; 286     B1  67.676768  7.161239868
#&gt; 287     B1  68.686869  7.058146319
#&gt; 288     B1  69.696970  6.955493978
#&gt; 289     B1  70.707071  6.853346953
#&gt; 290     B1  71.717172  6.751764620
#&gt; 291     B1  72.727273  6.650801882
#&gt; 292     B1  73.737374  6.550509419
#&gt; 293     B1  74.747475  6.450933922
#&gt; 294     B1  75.757576  6.352118318
#&gt; 295     B1  76.767677  6.254101979
#&gt; 296     B1  77.777778  6.156920928
#&gt; 297     B1  78.787879  6.060608023
#&gt; 298     B1  79.797980  5.965193142
#&gt; 299     B1  80.808081  5.870703355
#&gt; 300     B1  81.818182  5.777163083
#&gt; 301     B1  82.828283  5.684594257
#&gt; 302     B1  83.838384  5.593016458
#&gt; 303     B1  84.848485  5.502447062
#&gt; 304     B1  85.858586  5.412901366
#&gt; 305     B1  86.868687  5.324392718
#&gt; 306     B1  87.878788  5.236932630
#&gt; 307     B1  88.888889  5.150530889
#&gt; 308     B1  89.898990  5.065195670
#&gt; 309     B1  90.909091  4.980933628
#&gt; 310     B1  91.919192  4.897749999
#&gt; 311     B1  92.929293  4.815648688
#&gt; 312     B1  93.939394  4.734632351
#&gt; 313     B1  94.949495  4.654702481
#&gt; 314     B1  95.959596  4.575859481
#&gt; 315     B1  96.969697  4.498102737
#&gt; 316     B1  97.979798  4.421430686
#&gt; 317     B1  98.989899  4.345840882
#&gt; 318     B1 100.000000  4.271330056
#&gt; 319     C1   0.000000  0.000000000
#&gt; 320     C1   1.000000  1.829645786
#&gt; 321     C1   1.010101  1.847087763
#&gt; 322     C1   2.020202  3.492133303
#&gt; 323     C1   3.000000  4.910531064
#&gt; 324     C1   3.030303  4.951772742
#&gt; 325     C1   4.040404  6.241420142
#&gt; 326     C1   5.050505  7.375351980
#&gt; 327     C1   6.060606  8.366785999
#&gt; 328     C1   7.000000  9.171671206
#&gt; 329     C1   7.070707  9.227954769
#&gt; 330     C1   8.080808  9.970174354
#&gt; 331     C1   9.090909 10.603908370
#&gt; 332     C1  10.101010 11.138827767
#&gt; 333     C1  11.111111 11.583866567
#&gt; 334     C1  12.121212 11.947273869
#&gt; 335     C1  13.131313 12.236662337
#&gt; 336     C1  14.000000 12.431704739
#&gt; 337     C1  14.141414 12.459053419
#&gt; 338     C1  15.151515 12.620919488
#&gt; 339     C1  16.161616 12.728223141
#&gt; 340     C1  17.171717 12.786453805
#&gt; 341     C1  18.181818 12.800661859
#&gt; 342     C1  19.191919 12.775490422
#&gt; 343     C1  20.202020 12.715204956
#&gt; 344     C1  21.212121 12.623720845
#&gt; 345     C1  22.222222 12.504629065
#&gt; 346     C1  23.232323 12.361220091
#&gt; 347     C1  24.242424 12.196506142
#&gt; 348     C1  25.252525 12.013241882
#&gt; 349     C1  26.262626 11.813943686
#&gt; 350     C1  27.272727 11.600907551
#&gt; 351     C1  28.282828 11.376225763
#&gt; 352     C1  29.292929 11.141802382
#&gt; 353     C1  30.000000 10.972842888
#&gt; 354     C1  30.303030 10.899367648
#&gt; 355     C1  31.313131 10.650491354
#&gt; 356     C1  32.323232 10.396595286
#&gt; 357     C1  33.333333 10.138964763
#&gt; 358     C1  34.343434  9.878759358
#&gt; 359     C1  35.353535  9.617022857
#&gt; 360     C1  36.363636  9.354692485
#&gt; 361     C1  37.373737  9.092607481
#&gt; 362     C1  38.383838  8.831517041
#&gt; 363     C1  39.393939  8.572087685
#&gt; 364     C1  40.404040  8.314910084
#&gt; 365     C1  41.414141  8.060505385
#&gt; 366     C1  42.424242  7.809331068
#&gt; 367     C1  43.434343  7.561786371
#&gt; 368     C1  44.444444  7.318217302
#&gt; 369     C1  45.454545  7.078921287
#&gt; 370     C1  46.464646  6.844151456
#&gt; 371     C1  47.474747  6.614120611
#&gt; 372     C1  48.484848  6.389004885
#&gt; 373     C1  49.494949  6.168947129
#&gt; 374     C1  50.505051  5.954060026
#&gt; 375     C1  51.515152  5.744428970
#&gt; 376     C1  52.525253  5.540114721
#&gt; 377     C1  53.535354  5.341155842
#&gt; 378     C1  54.545455  5.147570951
#&gt; 379     C1  55.555556  4.959360784
#&gt; 380     C1  56.565657  4.776510102
#&gt; 381     C1  57.575758  4.598989433
#&gt; 382     C1  58.585859  4.426756673
#&gt; 383     C1  59.595960  4.259758556
#&gt; 384     C1  60.606061  4.097932000
#&gt; 385     C1  61.616162  3.941205338
#&gt; 386     C1  62.000000  3.882970158
#&gt; 387     C1  62.626263  3.789499444
#&gt; 388     C1  63.636364  3.642728760
#&gt; 389     C1  64.646465  3.500802233
#&gt; 390     C1  65.656566  3.363624171
#&gt; 391     C1  66.666667  3.231095021
#&gt; 392     C1  67.676768  3.103112069
#&gt; 393     C1  68.686869  2.979570086
#&gt; 394     C1  69.696970  2.860361903
#&gt; 395     C1  70.707071  2.745378939
#&gt; 396     C1  71.717172  2.634511667
#&gt; 397     C1  72.727273  2.527650041
#&gt; 398     C1  73.737374  2.424683880
#&gt; 399     C1  74.747475  2.325503203
#&gt; 400     C1  75.757576  2.229998536
#&gt; 401     C1  76.767677  2.138061182
#&gt; 402     C1  77.777778  2.049583458
#&gt; 403     C1  78.787879  1.964458908
#&gt; 404     C1  79.797980  1.882582485
#&gt; 405     C1  80.808081  1.803850715
#&gt; 406     C1  81.818182  1.728161832
#&gt; 407     C1  82.828283  1.655415900
#&gt; 408     C1  83.838384  1.585514911
#&gt; 409     C1  84.848485  1.518362874
#&gt; 410     C1  85.858586  1.453865880
#&gt; 411     C1  86.868687  1.391932162
#&gt; 412     C1  87.878788  1.332472134
#&gt; 413     C1  88.888889  1.275398429
#&gt; 414     C1  89.898990  1.220625918
#&gt; 415     C1  90.909091  1.168071723
#&gt; 416     C1  91.919192  1.117655227
#&gt; 417     C1  92.929293  1.069298066
#&gt; 418     C1  93.939394  1.022924125
#&gt; 419     C1  94.949495  0.978459525
#&gt; 420     C1  95.959596  0.935832597
#&gt; 421     C1  96.969697  0.894973866
#&gt; 422     C1  97.979798  0.855816021
#&gt; 423     C1  98.989899  0.818293881
#&gt; 424     C1 100.000000  0.782344364
#&gt; 425     A2   0.000000  0.000000000
#&gt; 426     A2   1.000000  0.005272357
#&gt; 427     A2   1.010101  0.005377817
#&gt; 428     A2   2.020202  0.020885524
#&gt; 429     A2   3.000000  0.044759575
#&gt; 430     A2   3.030303  0.045628064
#&gt; 431     A2   4.040404  0.078765936
#&gt; 432     A2   5.050505  0.119512155
#&gt; 433     A2   6.060606  0.167129381
#&gt; 434     A2   7.000000  0.216973934
#&gt; 435     A2   7.070707  0.220927189
#&gt; 436     A2   8.080808  0.280259484
#&gt; 437     A2   9.090909  0.344522046
#&gt; 438     A2  10.101010  0.413150206
#&gt; 439     A2  11.111111  0.485616641
#&gt; 440     A2  12.121212  0.561429288
#&gt; 441     A2  13.131313  0.640129357
#&gt; 442     A2  14.000000  0.709794102
#&gt; 443     A2  14.141414  0.721289460
#&gt; 444     A2  15.151515  0.804511827
#&gt; 445     A2  16.161616  0.889426625
#&gt; 446     A2  17.171717  0.975690359
#&gt; 447     A2  18.181818  1.062984358
#&gt; 448     A2  19.191919  1.151013342
#&gt; 449     A2  20.202020  1.239504068
#&gt; 450     A2  21.212121  1.328204041
#&gt; 451     A2  22.222222  1.416880297
#&gt; 452     A2  23.232323  1.505318253
#&gt; 453     A2  24.242424  1.593320615
#&gt; 454     A2  25.252525  1.680706344
#&gt; 455     A2  26.262626  1.767309680
#&gt; 456     A2  27.272727  1.852979219
#&gt; 457     A2  28.282828  1.937577034
#&gt; 458     A2  29.292929  2.020977853
#&gt; 459     A2  30.000000  2.078585030
#&gt; 460     A2  30.303030  2.103068270
#&gt; 461     A2  31.313131  2.183746011
#&gt; 462     A2  32.323232  2.262919231
#&gt; 463     A2  33.333333  2.340505852
#&gt; 464     A2  34.343434  2.416432940
#&gt; 465     A2  35.353535  2.490636111
#&gt; 466     A2  36.363636  2.563058979
#&gt; 467     A2  37.373737  2.633652622
#&gt; 468     A2  38.383838  2.702375089
#&gt; 469     A2  39.393939  2.769190926
#&gt; 470     A2  40.404040  2.834070737
#&gt; 471     A2  41.414141  2.896990764
#&gt; 472     A2  42.424242  2.957932489
#&gt; 473     A2  43.434343  3.016882265
#&gt; 474     A2  44.444444  3.073830964
#&gt; 475     A2  45.454545  3.128773647
#&gt; 476     A2  46.464646  3.181709250
#&gt; 477     A2  47.474747  3.232640290
#&gt; 478     A2  48.484848  3.281572591
#&gt; 479     A2  49.494949  3.328515022
#&gt; 480     A2  50.505051  3.373479253
#&gt; 481     A2  51.515152  3.416479521
#&gt; 482     A2  52.525253  3.457532417
#&gt; 483     A2  53.535354  3.496656681
#&gt; 484     A2  54.545455  3.533873012
#&gt; 485     A2  55.555556  3.569203883
#&gt; 486     A2  56.565657  3.602673379
#&gt; 487     A2  57.575758  3.634307034
#&gt; 488     A2  58.585859  3.664131686
#&gt; 489     A2  59.595960  3.692175334
#&gt; 490     A2  60.606061  3.718467012
#&gt; 491     A2  61.616162  3.743036663
#&gt; 492     A2  62.000000  3.751927986
#&gt; 493     A2  62.626263  3.765915028
#&gt; 494     A2  63.636364  3.787133539
#&gt; 495     A2  64.646465  3.806724217
#&gt; 496     A2  65.656566  3.824719582
#&gt; 497     A2  66.666667  3.841152565
#&gt; 498     A2  67.676768  3.856056426
#&gt; 499     A2  68.686869  3.869464684
#&gt; 500     A2  69.696970  3.881411040
#&gt; 501     A2  70.707071  3.891929316
#&gt; 502     A2  71.717172  3.901053396
#&gt; 503     A2  72.727273  3.908817168
#&gt; 504     A2  73.737374  3.915254472
#&gt; 505     A2  74.747475  3.920399054
#&gt; 506     A2  75.757576  3.924284521
#&gt; 507     A2  76.767677  3.926944303
#&gt; 508     A2  77.777778  3.928411610
#&gt; 509     A2  78.787879  3.928719404
#&gt; 510     A2  79.797980  3.927900364
#&gt; 511     A2  80.808081  3.925986861
#&gt; 512     A2  81.818182  3.923010926
#&gt; 513     A2  82.828283  3.919004234
#&gt; 514     A2  83.838384  3.913998077
#&gt; 515     A2  84.848485  3.908023347
#&gt; 516     A2  85.858586  3.901110518
#&gt; 517     A2  86.868687  3.893289633
#&gt; 518     A2  87.878788  3.884590288
#&gt; 519     A2  88.888889  3.875041619
#&gt; 520     A2  89.898990  3.864672297
#&gt; 521     A2  90.909091  3.853510511
#&gt; 522     A2  91.919192  3.841583970
#&gt; 523     A2  92.929293  3.828919886
#&gt; 524     A2  93.939394  3.815544978
#&gt; 525     A2  94.949495  3.801485462
#&gt; 526     A2  95.959596  3.786767051
#&gt; 527     A2  96.969697  3.771414951
#&gt; 528     A2  97.979798  3.755453860
#&gt; 529     A2  98.989899  3.738907968
#&gt; 530     A2 100.000000  3.721800959
#&gt; 
#&gt; $cost
#&gt; function (P) 
#&gt; {
#&gt;     assign(&quot;calls&quot;, calls + 1, inherits = TRUE)
#&gt;     if (trace_parms) 
#&gt;         cat(P, &quot;\n&quot;)
#&gt;     if (length(state.ini.optim) &gt; 0) {
#&gt;         odeini &lt;- c(P[1:length(state.ini.optim)], state.ini.fixed)
#&gt;         names(odeini) &lt;- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
#&gt;     }
#&gt;     else {
#&gt;         odeini &lt;- state.ini.fixed
#&gt;         names(odeini) &lt;- state.ini.fixed.boxnames
#&gt;     }
#&gt;     odeparms &lt;- c(P[(length(state.ini.optim) + 1):length(P)], 
#&gt;         transparms.fixed)
#&gt;     parms &lt;- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, 
#&gt;         transform_fractions = transform_fractions)
#&gt;     out &lt;- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, 
#&gt;         use_compiled = use_compiled, method.ode = method.ode, 
#&gt;         atol = atol, rtol = rtol, ...)
#&gt;     assign(&quot;out_predicted&quot;, out, inherits = TRUE)
#&gt;     mC &lt;- modCost(out, observed, y = &quot;value&quot;, err = err, weight = weight, 
#&gt;         scaleVar = scaleVar)
#&gt;     if (mC$model &lt; cost.old) {
#&gt;         if (!quiet) 
#&gt;             cat(&quot;Model cost at call &quot;, calls, &quot;: &quot;, mC$model, 
#&gt;                 &quot;\n&quot;)
#&gt;         if (plot) {
#&gt;             outtimes_plot = seq(min(observed$time), max(observed$time), 
#&gt;                 length.out = 100)
#&gt;             out_plot &lt;- mkinpredict(mkinmod, parms, odeini, outtimes_plot, 
#&gt;                 solution_type = solution_type, use_compiled = use_compiled, 
#&gt;                 method.ode = method.ode, atol = atol, rtol = rtol, 
#&gt;                 ...)
#&gt;             plot(0, type = &quot;n&quot;, xlim = range(observed$time), 
#&gt;                 ylim = c(0, max(observed$value, na.rm = TRUE)), 
#&gt;                 xlab = &quot;Time&quot;, ylab = &quot;Observed&quot;)
#&gt;             col_obs &lt;- pch_obs &lt;- 1:length(obs_vars)
#&gt;             lty_obs &lt;- rep(1, length(obs_vars))
#&gt;             names(col_obs) &lt;- names(pch_obs) &lt;- names(lty_obs) &lt;- obs_vars
#&gt;             for (obs_var in obs_vars) {
#&gt;                 points(subset(observed, name == obs_var, c(time, 
#&gt;                   value)), pch = pch_obs[obs_var], col = col_obs[obs_var])
#&gt;             }
#&gt;             matlines(out_plot$time, out_plot[-1], col = col_obs, 
#&gt;                 lty = lty_obs)
#&gt;             legend(&quot;topright&quot;, inset = c(0.05, 0.05), legend = obs_vars, 
#&gt;                 col = col_obs, pch = pch_obs, lty = 1:length(pch_obs))
#&gt;         }
#&gt;         assign(&quot;cost.old&quot;, mC$model, inherits = TRUE)
#&gt;     }
#&gt;     return(mC)
#&gt; }
#&gt; &lt;environment: 0x36a83b0&gt;
#&gt; 
#&gt; $cost_notrans
#&gt; function (P) 
#&gt; {
#&gt;     if (length(state.ini.optim) &gt; 0) {
#&gt;         odeini &lt;- c(P[1:length(state.ini.optim)], state.ini.fixed)
#&gt;         names(odeini) &lt;- c(state.ini.optim.boxnames, state.ini.fixed.boxnames)
#&gt;     }
#&gt;     else {
#&gt;         odeini &lt;- state.ini.fixed
#&gt;         names(odeini) &lt;- state.ini.fixed.boxnames
#&gt;     }
#&gt;     odeparms &lt;- c(P[(length(state.ini.optim) + 1):length(P)], 
#&gt;         parms.fixed)
#&gt;     out &lt;- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, 
#&gt;         use_compiled = use_compiled, method.ode = method.ode, 
#&gt;         atol = atol, rtol = rtol, ...)
#&gt;     mC &lt;- modCost(out, observed, y = &quot;value&quot;, err = err, weight = weight, 
#&gt;         scaleVar = scaleVar)
#&gt;     return(mC)
#&gt; }
#&gt; &lt;environment: 0x36a83b0&gt;
#&gt; 
#&gt; $hessian_notrans
#&gt;                    parent_0     k_parent          k_A1          k_B1
#&gt; parent_0           7.365081   -1854.5113 -7.186039e+02 -1.307858e+02
#&gt; k_parent       -1854.511330 2686790.7676 -6.235542e+04 -1.429363e+04
#&gt; k_A1            -718.603865  -62355.4211  3.128242e+06  0.000000e+00
#&gt; k_B1            -130.785796  -14293.6348  0.000000e+00  4.545506e+05
#&gt; k_C1             -76.404274  -38575.9391  1.190516e-02 -9.422820e-04
#&gt; k_A2             -17.933942   -4390.5079 -5.838973e+04  0.000000e+00
#&gt; f_parent_to_A1    75.150866   43257.2599 -1.733841e+05  0.000000e+00
#&gt; f_parent_to_B1    29.265575   17940.1132  0.000000e+00 -6.150198e+04
#&gt; f_parent_to_C1    20.661354   19692.5582 -6.146186e-05 -1.990817e-03
#&gt; f_A1_to_A2         1.593279     597.0744  5.849840e+03  0.000000e+00
#&gt;                         k_C1          k_A2 f_parent_to_A1 f_parent_to_B1
#&gt; parent_0       -7.640427e+01 -1.793394e+01   7.515087e+01   2.926558e+01
#&gt; k_parent       -3.857594e+04 -4.390508e+03   4.325726e+04   1.794011e+04
#&gt; k_A1            1.190516e-02 -5.838973e+04  -1.733841e+05   0.000000e+00
#&gt; k_B1           -9.422820e-04  0.000000e+00   0.000000e+00  -6.150198e+04
#&gt; k_C1            8.855106e+04  4.105787e-04  -1.354551e-03   5.852620e-04
#&gt; k_A2            4.105787e-04  4.649850e+04  -4.327086e+03   0.000000e+00
#&gt; f_parent_to_A1 -1.354551e-03 -4.327086e+03   1.813234e+04   0.000000e+00
#&gt; f_parent_to_B1  5.852620e-04  0.000000e+00   0.000000e+00   1.376213e+04
#&gt; f_parent_to_C1 -1.658031e+04  2.903794e-04   1.946385e-03   1.325258e-03
#&gt; f_A1_to_A2     -4.367402e-05 -3.679910e+03   3.844249e+02   0.000000e+00
#&gt;                f_parent_to_C1    f_A1_to_A2
#&gt; parent_0         2.066135e+01  1.593279e+00
#&gt; k_parent         1.969256e+04  5.970744e+02
#&gt; k_A1            -6.146186e-05  5.849840e+03
#&gt; k_B1            -1.990817e-03  0.000000e+00
#&gt; k_C1            -1.658031e+04 -4.367402e-05
#&gt; k_A2             2.903794e-04 -3.679910e+03
#&gt; f_parent_to_A1   1.946385e-03  3.844249e+02
#&gt; f_parent_to_B1   1.325258e-03  0.000000e+00
#&gt; f_parent_to_C1   4.483759e+03 -3.796730e-05
#&gt; f_A1_to_A2      -3.796730e-05  3.269288e+02
#&gt; 
#&gt; $start
#&gt;                     value   type
#&gt; parent_0       93.2000000  state
#&gt; k_parent        0.1000000 deparm
#&gt; k_A1            0.1001000 deparm
#&gt; k_B1            0.1002000 deparm
#&gt; k_C1            0.1003000 deparm
#&gt; k_A2            0.1004000 deparm
#&gt; f_parent_to_A1  0.3333333 deparm
#&gt; f_parent_to_B1  0.3333333 deparm
#&gt; f_parent_to_C1  0.3333333 deparm
#&gt; f_A1_to_A2      0.5000000 deparm
#&gt; 
#&gt; $start_transformed
#&gt;                    value lower upper
#&gt; parent_0       93.200000  -Inf   Inf
#&gt; log_k_parent   -2.302585  -Inf   Inf
#&gt; log_k_A1       -2.301586  -Inf   Inf
#&gt; log_k_B1       -2.300587  -Inf   Inf
#&gt; log_k_C1       -2.299590  -Inf   Inf
#&gt; log_k_A2       -2.298593  -Inf   Inf
#&gt; f_parent_ilr_1  0.000000  -Inf   Inf
#&gt; f_parent_ilr_2  0.000000  -Inf   Inf
#&gt; f_A1_ilr_1      0.000000  -Inf   Inf
#&gt; 
#&gt; $fixed
#&gt;      value  type
#&gt; A1_0     0 state
#&gt; B1_0     0 state
#&gt; C1_0     0 state
#&gt; A2_0     0 state
#&gt; 
#&gt; $data
#&gt;    time variable observed    predicted   residual
#&gt; 1     0   parent    93.20 91.918159794  1.2818402
#&gt; 2     1   parent    89.40 87.462788491  1.9372115
#&gt; 3     3   parent    79.70 79.189448055  0.5105519
#&gt; 4     7   parent    61.10 64.916531757 -3.8165318
#&gt; 5    14   parent    48.20 45.846828365  2.3531716
#&gt; 6    30   parent    15.90 20.704334210 -4.8043342
#&gt; 7    62   parent     6.50  4.222456793  2.2775432
#&gt; 8   100   parent     6.00  0.639147580  5.3608524
#&gt; 9     0       A1       NA  0.000000000         NA
#&gt; 10    1       A1       NA  1.685461006         NA
#&gt; 11    3       A1     0.55  4.746752202 -4.1967522
#&gt; 12    7       A1     6.87  9.773298725 -2.9032987
#&gt; 13   14       A1    17.08 15.767512526  1.3124875
#&gt; 14   30       A1    21.68 21.077890710  0.6021093
#&gt; 15   62       A1    15.77 18.279232408 -2.5092324
#&gt; 16  100       A1    13.63 11.743860400  1.8861396
#&gt; 17    0       B1       NA  0.000000000         NA
#&gt; 18    1       B1       NA  0.862762059         NA
#&gt; 19    3       B1       NA  2.418226457         NA
#&gt; 20    7       B1     0.55  4.930176837 -4.3801768
#&gt; 21   14       B1     2.31  7.810248132 -5.5002481
#&gt; 22   30       B1    15.76  9.968281596  5.7917184
#&gt; 23   62       B1     6.36  7.745265792 -1.3852658
#&gt; 24  100       B1     3.74  4.271330056 -0.5313301
#&gt; 25    0       C1       NA  0.000000000         NA
#&gt; 26    1       C1     0.55  1.829645786 -1.2796458
#&gt; 27    3       C1     3.20  4.910531064 -1.7105311
#&gt; 28    7       C1     5.46  9.171671206 -3.7116712
#&gt; 29   14       C1    12.55 12.431704739  0.1182953
#&gt; 30   30       C1    10.45 10.972842888 -0.5228429
#&gt; 31   62       C1     4.74  3.882970158  0.8570298
#&gt; 32  100       C1     4.33  0.782344364  3.5476556
#&gt; 33    0       A2       NA  0.000000000         NA
#&gt; 34    1       A2     0.55  0.005272357  0.5447276
#&gt; 35    3       A2     1.41  0.044759575  1.3652404
#&gt; 36    7       A2     0.55  0.216973934  0.3330261
#&gt; 37   14       A2     1.29  0.709794102  0.5802059
#&gt; 38   30       A2     1.95  2.078585030 -0.1285850
#&gt; 39   62       A2     3.54  3.751927986 -0.2119280
#&gt; 40  100       A2     3.86  3.721800959  0.1381990
#&gt; 
#&gt; $atol
#&gt; [1] 1e-08
#&gt; 
#&gt; $rtol
#&gt; [1] 1e-10
#&gt; 
#&gt; $weight.ini
#&gt; [1] &quot;none&quot;
#&gt; 
#&gt; $reweight.tol
#&gt; [1] 1e-08
#&gt; 
#&gt; $reweight.max.iter
#&gt; [1] 10
#&gt; 
#&gt; $bparms.optim
#&gt;       parent_0       k_parent           k_A1           k_B1           k_C1 
#&gt;    91.91815979     0.04968519     0.01393165     0.01859846     0.06171564 
#&gt;           k_A2 f_parent_to_A1 f_parent_to_B1 f_parent_to_C1     f_A1_to_A2 
#&gt;     0.02431549     0.38096192     0.19546676     0.42357132     0.44796066 
#&gt; 
#&gt; $bparms.fixed
#&gt; A1_0 B1_0 C1_0 A2_0 
#&gt;    0    0    0    0 
#&gt; 
#&gt; $bparms.ode
#&gt;       k_parent f_parent_to_A1 f_parent_to_B1 f_parent_to_C1           k_A1 
#&gt;     0.04968519     0.38096192     0.19546676     0.42357132     0.01393165 
#&gt;     f_A1_to_A2           k_B1           k_C1           k_A2 
#&gt;     0.44796066     0.01859846     0.06171564     0.02431549 
#&gt; 
#&gt; $bparms.state
#&gt;   parent       A1       B1       C1       A2 
#&gt; 91.91816  0.00000  0.00000  0.00000  0.00000 
#&gt; 
#&gt; $date
#&gt; [1] &quot;Fri Nov 18 15:20:45 2016&quot;
#&gt; 
#&gt; attr(,&quot;class&quot;)
#&gt; [1] &quot;mkinfit&quot; &quot;modFit&quot; </div></pre>
  </div>
  <div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
    <h2>Contents</h2>
    <ul class="nav nav-pills nav-stacked">
      
      <li><a href="#format">Format</a></li>

      <li><a href="#references">References</a></li>
      
      <li><a href="#examples">Examples</a></li>
    </ul>

  </div>
</div>

      <footer>
      <div class="copyright">
  <p>Developed by Johannes Ranke.</p>
</div>

<div class="pkgdown">
  <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
</div>

      </footer>
   </div>

  </body>
</html>

Contact - Imprint