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authorJohannes Ranke <jranke@uni-bremen.de>2016-11-18 15:01:53 +0100
committerJohannes Ranke <jranke@uni-bremen.de>2016-11-18 15:22:42 +0100
commitc6086d1dd97ad2d6420625de7b8009b1b0f85d06 (patch)
tree1a38fd690c94a556555ec71edff443bcfe609b7b /docs/reference/schaefer07_complex_case.html
parent9a8dfa8bd52664929fd4197f3e9c4e65b62cad53 (diff)
Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE)
Using branch 'jranke' on jranke/pkgdown, fixing issues hadley/pgkdown#178 and hadley/pkgdown#213 Remove plot=TRUE from mkinfit calls also in dontrun sections of examples to avoid a flood png files documenting the progress of the fit.
Diffstat (limited to 'docs/reference/schaefer07_complex_case.html')
-rw-r--r--docs/reference/schaefer07_complex_case.html1054
1 files changed, 1053 insertions, 1 deletions
diff --git a/docs/reference/schaefer07_complex_case.html b/docs/reference/schaefer07_complex_case.html
index e2f845d9..9bb6d4ee 100644
--- a/docs/reference/schaefer07_complex_case.html
+++ b/docs/reference/schaefer07_complex_case.html
@@ -116,7 +116,1059 @@
<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='co'>## Not run: mkinfit(model, data, plot=TRUE)</span></div></pre>
+ <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
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+#&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>
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<h2>Contents</h2>

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