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+ <h1>Subsetting method for mmkin objects</h1>
+ </div>
+
+
+ <p>Subsetting method for mmkin objects.</p>
+
+
+ <pre># S3 method for mmkin
+[(x, i, j, ..., drop = FALSE)</pre>
+
+ <h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a> Arguments</h2>
+ <dl class="dl-horizontal">
+ <dt>x</dt>
+ <dd>An <code><a href='mmkin.html'>mmkin</a> object</code></dd>
+ <dt>i</dt>
+ <dd>Row index selecting the fits for specific models</dd>
+ <dt>j</dt>
+ <dd>Column index selecting the fits to specific datasets</dd>
+ <dt>...</dt>
+ <dd>Not used, only there to satisfy the generic method definition</dd>
+ <dt>drop</dt>
+ <dd>If FALSE, the method always returns an mmkin object, otherwise either
+ a list of mkinfit objects or a single mkinfit object.</dd>
+ </dl>
+
+ <h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
+
+ <p>An object of class <code><a href='mmkin.html'>mmkin</a></code>.</p>
+
+
+ <h2 class="hasAnchor" id="examples">
+ <a class="anchor" href="#examples"></a>
+ Examples
+ </h2>
+ <pre class="examples"><div class='input'> <span class='co'># Only use one core, to pass R CMD check --as-cran</span>
+ <span class='no'>fits</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mmkin.html'>mmkin</a></span>(<span class='fu'>c</span>(<span class='st'>"SFO"</span>, <span class='st'>"FOMC"</span>), <span class='fu'>list</span>(<span class='kw'>B</span> <span class='kw'>=</span> <span class='no'>FOCUS_2006_B</span>, <span class='kw'>C</span> <span class='kw'>=</span> <span class='no'>FOCUS_2006_C</span>),
+ <span class='kw'>cores</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
+ <span class='no'>fits</span>[<span class='st'>"FOMC"</span>, ]</div><div class='output co'>#&gt; dataset
+#&gt; model B C
+#&gt; FOMC List,42 List,42
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mmkin&quot;
+#&gt; </div><div class='input'> <span class='no'>fits</span>[, <span class='st'>"B"</span>]</div><div class='output co'>#&gt; dataset
+#&gt; model B
+#&gt; SFO List,42
+#&gt; FOMC List,42
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mmkin&quot;
+#&gt; </div><div class='input'> <span class='no'>fits</span>[, <span class='st'>"B"</span>, <span class='kw'>drop</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>]$<span class='no'>FOMC</span></div><div class='output co'>#&gt; $par
+#&gt; parent_0 log_alpha log_beta
+#&gt; 99.666193 2.549849 5.050586
+#&gt;
+#&gt; $ssr
+#&gt; [1] 28.58291
+#&gt;
+#&gt; $convergence
+#&gt; [1] 0
+#&gt;
+#&gt; $iterations
+#&gt; [1] 21
+#&gt;
+#&gt; $evaluations
+#&gt; function gradient
+#&gt; 25 78
+#&gt;
+#&gt; $counts
+#&gt; [1] &quot;both X-convergence and relative convergence (5)&quot;
+#&gt;
+#&gt; $hessian
+#&gt; parent_0 log_alpha log_beta
+#&gt; parent_0 4.123033 -95.69983 93.17699
+#&gt; log_alpha -95.699832 6618.85833 -6352.46648
+#&gt; log_beta 93.176993 -6352.46648 6101.23483
+#&gt;
+#&gt; $residuals
+#&gt; parent parent parent parent parent parent
+#&gt; 1.046192647 -3.322396479 3.655156669 -1.705316770 0.406306255 -0.123734689
+#&gt; parent parent
+#&gt; -0.036886982 -0.006240458
+#&gt;
+#&gt; $ms
+#&gt; [1] 3.572863
+#&gt;
+#&gt; $var_ms
+#&gt; parent
+#&gt; 3.572863
+#&gt;
+#&gt; $var_ms_unscaled
+#&gt; parent
+#&gt; 3.572863
+#&gt;
+#&gt; $var_ms_unweighted
+#&gt; parent
+#&gt; 3.572863
+#&gt;
+#&gt; $rank
+#&gt; [1] 3
+#&gt;
+#&gt; $df.residual
+#&gt; [1] 5
+#&gt;
+#&gt; $solution_type
+#&gt; [1] &quot;analytical&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] 111
+#&gt;
+#&gt; $time
+#&gt; user system elapsed
+#&gt; 0.26 0.00 0.26
+#&gt;
+#&gt; $mkinmod
+#&gt; &lt;mkinmod&gt; model generated with
+#&gt; Use of formation fractions $use_of_ff: min
+#&gt; Specification $spec:
+#&gt; $parent
+#&gt; $type: FOMC; $sink: TRUE
+#&gt;
+#&gt; $observed
+#&gt; name time value
+#&gt; 1 parent 0 98.62
+#&gt; 2 parent 3 81.43
+#&gt; 3 parent 7 53.18
+#&gt; 4 parent 14 34.89
+#&gt; 5 parent 30 10.09
+#&gt; 6 parent 62 1.50
+#&gt; 7 parent 90 0.33
+#&gt; 8 parent 118 0.08
+#&gt;
+#&gt; $obs_vars
+#&gt; [1] &quot;parent&quot;
+#&gt;
+#&gt; $predicted
+#&gt; name time value
+#&gt; 1 parent 0.000000 99.66619265
+#&gt; 2 parent 1.191919 90.41690342
+#&gt; 3 parent 2.383838 82.08630014
+#&gt; 4 parent 3.000000 78.10760352
+#&gt; 5 parent 3.575758 74.57722848
+#&gt; 6 parent 4.767677 67.80342415
+#&gt; 7 parent 5.959596 61.68822425
+#&gt; 8 parent 7.000000 56.83515667
+#&gt; 9 parent 7.151515 56.16343898
+#&gt; 10 parent 8.343434 51.16836285
+#&gt; 11 parent 9.535354 46.64890734
+#&gt; 12 parent 10.727273 42.55683931
+#&gt; 13 parent 11.919192 38.84911158
+#&gt; 14 parent 13.111111 35.48727414
+#&gt; 15 parent 14.000000 33.18468323
+#&gt; 16 parent 14.303030 32.43695565
+#&gt; 17 parent 15.494949 29.66740651
+#&gt; 18 parent 16.686869 27.15109578
+#&gt; 19 parent 17.878788 24.86335532
+#&gt; 20 parent 19.070707 22.78206538
+#&gt; 21 parent 20.262626 20.88737647
+#&gt; 22 parent 21.454545 19.16146324
+#&gt; 23 parent 22.646465 17.58830644
+#&gt; 24 parent 23.838384 16.15349953
+#&gt; 25 parent 25.030303 14.84407724
+#&gt; 26 parent 26.222222 13.64836315
+#&gt; 27 parent 27.414141 12.55583436
+#&gt; 28 parent 28.606061 11.55700107
+#&gt; 29 parent 29.797980 10.64329940
+#&gt; 30 parent 30.000000 10.49630626
+#&gt; 31 parent 30.989899 9.80699593
+#&gt; 32 parent 32.181818 9.04110261
+#&gt; 33 parent 33.373737 8.33930082
+#&gt; 34 parent 34.565657 7.69587362
+#&gt; 35 parent 35.757576 7.10564515
+#&gt; 36 parent 36.949495 6.56392657
+#&gt; 37 parent 38.141414 6.06646759
+#&gt; 38 parent 39.333333 5.60941311
+#&gt; 39 parent 40.525253 5.18926438
+#&gt; 40 parent 41.717172 4.80284421
+#&gt; 41 parent 42.909091 4.44726569
+#&gt; 42 parent 44.101010 4.11990420
+#&gt; 43 parent 45.292929 3.81837216
+#&gt; 44 parent 46.484848 3.54049644
+#&gt; 45 parent 47.676768 3.28429799
+#&gt; 46 parent 48.868687 3.04797350
+#&gt; 47 parent 50.060606 2.82987892
+#&gt; 48 parent 51.252525 2.62851456
+#&gt; 49 parent 52.444444 2.44251172
+#&gt; 50 parent 53.636364 2.27062056
+#&gt; 51 parent 54.828283 2.11169922
+#&gt; 52 parent 56.020202 1.96470393
+#&gt; 53 parent 57.212121 1.82868009
+#&gt; 54 parent 58.404040 1.70275424
+#&gt; 55 parent 59.595960 1.58612677
+#&gt; 56 parent 60.787879 1.47806529
+#&gt; 57 parent 61.979798 1.37789865
+#&gt; 58 parent 62.000000 1.37626531
+#&gt; 59 parent 63.171717 1.28501157
+#&gt; 60 parent 64.363636 1.19883967
+#&gt; 61 parent 65.555556 1.11886504
+#&gt; 62 parent 66.747475 1.04461220
+#&gt; 63 parent 67.939394 0.97564441
+#&gt; 64 parent 69.131313 0.91156031
+#&gt; 65 parent 70.323232 0.85199096
+#&gt; 66 parent 71.515152 0.79659697
+#&gt; 67 parent 72.707071 0.74506609
+#&gt; 68 parent 73.898990 0.69711084
+#&gt; 69 parent 75.090909 0.65246649
+#&gt; 70 parent 76.282828 0.61088912
+#&gt; 71 parent 77.474747 0.57215389
+#&gt; 72 parent 78.666667 0.53605348
+#&gt; 73 parent 79.858586 0.50239663
+#&gt; 74 parent 81.050505 0.47100683
+#&gt; 75 parent 82.242424 0.44172111
+#&gt; 76 parent 83.434343 0.41438896
+#&gt; 77 parent 84.626263 0.38887128
+#&gt; 78 parent 85.818182 0.36503953
+#&gt; 79 parent 87.010101 0.34277481
+#&gt; 80 parent 88.202020 0.32196716
+#&gt; 81 parent 89.393939 0.30251479
+#&gt; 82 parent 90.000000 0.29311302
+#&gt; 83 parent 90.585859 0.28432347
+#&gt; 84 parent 91.777778 0.26730596
+#&gt; 85 parent 92.969697 0.25138141
+#&gt; 86 parent 94.161616 0.23647487
+#&gt; 87 parent 95.353535 0.22251689
+#&gt; 88 parent 96.545455 0.20944302
+#&gt; 89 parent 97.737374 0.19719349
+#&gt; 90 parent 98.929293 0.18571281
+#&gt; 91 parent 100.121212 0.17494947
+#&gt; 92 parent 101.313131 0.16485560
+#&gt; 93 parent 102.505051 0.15538676
+#&gt; 94 parent 103.696970 0.14650163
+#&gt; 95 parent 104.888889 0.13816179
+#&gt; 96 parent 106.080808 0.13033150
+#&gt; 97 parent 107.272727 0.12297753
+#&gt; 98 parent 108.464646 0.11606895
+#&gt; 99 parent 109.656566 0.10957695
+#&gt; 100 parent 110.848485 0.10347470
+#&gt; 101 parent 112.040404 0.09773723
+#&gt; 102 parent 113.232323 0.09234125
+#&gt; 103 parent 114.424242 0.08726506
+#&gt; 104 parent 115.616162 0.08248842
+#&gt; 105 parent 116.808081 0.07799245
+#&gt; 106 parent 118.000000 0.07375954
+#&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: 0x5421f48&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: 0x5421f48&gt;
+#&gt;
+#&gt; $hessian_notrans
+#&gt; parent_0 alpha beta
+#&gt; parent_0 4.1230329 -7.473531 0.5968527
+#&gt; alpha -7.4735307 40.365690 -3.1777189
+#&gt; beta 0.5968527 -3.177719 0.2503425
+#&gt;
+#&gt; $start
+#&gt; value type
+#&gt; parent_0 98.62 state
+#&gt; alpha 1.00 deparm
+#&gt; beta 10.00 deparm
+#&gt;
+#&gt; $start_transformed
+#&gt; value lower upper
+#&gt; parent_0 98.620000 -Inf Inf
+#&gt; log_alpha 0.000000 -Inf Inf
+#&gt; log_beta 2.302585 -Inf Inf
+#&gt;
+#&gt; $fixed
+#&gt; [1] value type
+#&gt; &lt;0 rows&gt; (or 0-length row.names)
+#&gt;
+#&gt; $data
+#&gt; time variable observed predicted residual
+#&gt; 1 0 parent 98.62 99.66619265 -1.046192647
+#&gt; 2 3 parent 81.43 78.10760352 3.322396479
+#&gt; 3 7 parent 53.18 56.83515667 -3.655156669
+#&gt; 4 14 parent 34.89 33.18468323 1.705316770
+#&gt; 5 30 parent 10.09 10.49630626 -0.406306255
+#&gt; 6 62 parent 1.50 1.37626531 0.123734689
+#&gt; 7 90 parent 0.33 0.29311302 0.036886982
+#&gt; 8 118 parent 0.08 0.07375954 0.006240458
+#&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 alpha beta
+#&gt; 99.66619 12.80517 156.11390
+#&gt;
+#&gt; $bparms.fixed
+#&gt; numeric(0)
+#&gt;
+#&gt; $bparms.ode
+#&gt; alpha beta
+#&gt; 12.80517 156.11390
+#&gt;
+#&gt; $bparms.state
+#&gt; parent
+#&gt; 99.66619
+#&gt;
+#&gt; $date
+#&gt; [1] &quot;Wed Oct 26 23:50:33 2016&quot;
+#&gt;
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mkinfit&quot; &quot;modFit&quot;
+#&gt; </div><div class='input'> <span class='no'>fits</span>[<span class='st'>"SFO"</span>, <span class='st'>"B"</span>]</div><div class='output co'>#&gt; dataset
+#&gt; model B
+#&gt; SFO List,42
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mmkin&quot;
+#&gt; </div><div class='input'> <span class='no'>fits</span><span class='kw'>[[</span><span class='st'>"SFO"</span>, <span class='st'>"B"</span>]] <span class='co'># This is equivalent to</span></div><div class='output co'>#&gt; $par
+#&gt; parent_0 log_k_parent_sink
+#&gt; 99.174072 -2.549028
+#&gt;
+#&gt; $ssr
+#&gt; [1] 30.65564
+#&gt;
+#&gt; $convergence
+#&gt; [1] 0
+#&gt;
+#&gt; $iterations
+#&gt; [1] 5
+#&gt;
+#&gt; $evaluations
+#&gt; function gradient
+#&gt; 8 15
+#&gt;
+#&gt; $counts
+#&gt; [1] &quot;relative convergence (4)&quot;
+#&gt;
+#&gt; $hessian
+#&gt; parent_0 log_k_parent_sink
+#&gt; parent_0 4.163631 -94.09343
+#&gt; log_k_parent_sink -94.093431 6311.34610
+#&gt;
+#&gt; $residuals
+#&gt; parent parent parent parent parent parent
+#&gt; 0.55407218 -2.98452128 4.20445742 -1.68599939 -0.58185357 -0.72033730
+#&gt; parent parent
+#&gt; -0.24260405 -0.07020339
+#&gt;
+#&gt; $ms
+#&gt; [1] 3.831956
+#&gt;
+#&gt; $var_ms
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $var_ms_unscaled
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $var_ms_unweighted
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $rank
+#&gt; [1] 2
+#&gt;
+#&gt; $df.residual
+#&gt; [1] 6
+#&gt;
+#&gt; $solution_type
+#&gt; [1] &quot;analytical&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] 29
+#&gt;
+#&gt; $time
+#&gt; user system elapsed
+#&gt; 0.068 0.000 0.070
+#&gt;
+#&gt; $mkinmod
+#&gt; &lt;mkinmod&gt; model generated with
+#&gt; Use of formation fractions $use_of_ff: min
+#&gt; Specification $spec:
+#&gt; $parent
+#&gt; $type: SFO; $sink: TRUE
+#&gt; Coefficient matrix $coefmat available
+#&gt;
+#&gt; $observed
+#&gt; name time value
+#&gt; 1 parent 0 98.62
+#&gt; 2 parent 3 81.43
+#&gt; 3 parent 7 53.18
+#&gt; 4 parent 14 34.89
+#&gt; 5 parent 30 10.09
+#&gt; 6 parent 62 1.50
+#&gt; 7 parent 90 0.33
+#&gt; 8 parent 118 0.08
+#&gt;
+#&gt; $obs_vars
+#&gt; [1] &quot;parent&quot;
+#&gt;
+#&gt; $predicted
+#&gt; name time value
+#&gt; 1 parent 0.000000 99.17407218
+#&gt; 2 parent 1.191919 90.35253561
+#&gt; 3 parent 2.383838 82.31567498
+#&gt; 4 parent 3.000000 78.44547872
+#&gt; 5 parent 3.575758 74.99369333
+#&gt; 6 parent 4.767677 68.32300215
+#&gt; 7 parent 5.959596 62.24566915
+#&gt; 8 parent 7.000000 57.38445742
+#&gt; 9 parent 7.151515 56.70891509
+#&gt; 10 parent 8.343434 51.66465547
+#&gt; 11 parent 9.535354 47.06908288
+#&gt; 12 parent 10.727273 42.88228661
+#&gt; 13 parent 11.919192 39.06790599
+#&gt; 14 parent 13.111111 35.59281463
+#&gt; 15 parent 14.000000 33.20400061
+#&gt; 16 parent 14.303030 32.42683275
+#&gt; 17 parent 15.494949 29.54246504
+#&gt; 18 parent 16.686869 26.91466193
+#&gt; 19 parent 17.878788 24.52060198
+#&gt; 20 parent 19.070707 22.33949373
+#&gt; 21 parent 20.262626 20.35239512
+#&gt; 22 parent 21.454545 18.54204899
+#&gt; 23 parent 22.646465 16.89273320
+#&gt; 24 parent 23.838384 15.39012410
+#&gt; 25 parent 25.030303 14.02117212
+#&gt; 26 parent 26.222222 12.77398846
+#&gt; 27 parent 27.414141 11.63774182
+#&gt; 28 parent 28.606061 10.60256435
+#&gt; 29 parent 29.797980 9.65946594
+#&gt; 30 parent 30.000000 9.50814643
+#&gt; 31 parent 30.989899 8.80025617
+#&gt; 32 parent 32.181818 8.01747313
+#&gt; 33 parent 33.373737 7.30431867
+#&gt; 34 parent 34.565657 6.65459931
+#&gt; 35 parent 35.757576 6.06267251
+#&gt; 36 parent 36.949495 5.52339762
+#&gt; 37 parent 38.141414 5.03209124
+#&gt; 38 parent 39.333333 4.58448658
+#&gt; 39 parent 40.525253 4.17669637
+#&gt; 40 parent 41.717172 3.80517911
+#&gt; 41 parent 42.909091 3.46670832
+#&gt; 42 parent 44.101010 3.15834451
+#&gt; 43 parent 45.292929 2.87740968
+#&gt; 44 parent 46.484848 2.62146400
+#&gt; 45 parent 47.676768 2.38828471
+#&gt; 46 parent 48.868687 2.17584671
+#&gt; 47 parent 50.060606 1.98230508
+#&gt; 48 parent 51.252525 1.80597899
+#&gt; 49 parent 52.444444 1.64533711
+#&gt; 50 parent 53.636364 1.49898432
+#&gt; 51 parent 54.828283 1.36564963
+#&gt; 52 parent 56.020202 1.24417505
+#&gt; 53 parent 57.212121 1.13350565
+#&gt; 54 parent 58.404040 1.03268029
+#&gt; 55 parent 59.595960 0.94082335
+#&gt; 56 parent 60.787879 0.85713708
+#&gt; 57 parent 61.979798 0.78089471
+#&gt; 58 parent 62.000000 0.77966270
+#&gt; 59 parent 63.171717 0.71143411
+#&gt; 60 parent 64.363636 0.64815202
+#&gt; 61 parent 65.555556 0.59049888
+#&gt; 62 parent 66.747475 0.53797399
+#&gt; 63 parent 67.939394 0.49012119
+#&gt; 64 parent 69.131313 0.44652489
+#&gt; 65 parent 70.323232 0.40680649
+#&gt; 66 parent 71.515152 0.37062104
+#&gt; 67 parent 72.707071 0.33765429
+#&gt; 68 parent 73.898990 0.30761993
+#&gt; 69 parent 75.090909 0.28025713
+#&gt; 70 parent 76.282828 0.25532825
+#&gt; 71 parent 77.474747 0.23261679
+#&gt; 72 parent 78.666667 0.21192552
+#&gt; 73 parent 79.858586 0.19307474
+#&gt; 74 parent 81.050505 0.17590074
+#&gt; 75 parent 82.242424 0.16025436
+#&gt; 76 parent 83.434343 0.14599973
+#&gt; 77 parent 84.626263 0.13301305
+#&gt; 78 parent 85.818182 0.12118154
+#&gt; 79 parent 87.010101 0.11040244
+#&gt; 80 parent 88.202020 0.10058214
+#&gt; 81 parent 89.393939 0.09163535
+#&gt; 82 parent 90.000000 0.08739595
+#&gt; 83 parent 90.585859 0.08348439
+#&gt; 84 parent 91.777778 0.07605845
+#&gt; 85 parent 92.969697 0.06929305
+#&gt; 86 parent 94.161616 0.06312943
+#&gt; 87 parent 95.353535 0.05751406
+#&gt; 88 parent 96.545455 0.05239819
+#&gt; 89 parent 97.737374 0.04773737
+#&gt; 90 parent 98.929293 0.04349113
+#&gt; 91 parent 100.121212 0.03962259
+#&gt; 92 parent 101.313131 0.03609816
+#&gt; 93 parent 102.505051 0.03288723
+#&gt; 94 parent 103.696970 0.02996191
+#&gt; 95 parent 104.888889 0.02729679
+#&gt; 96 parent 106.080808 0.02486874
+#&gt; 97 parent 107.272727 0.02265667
+#&gt; 98 parent 108.464646 0.02064136
+#&gt; 99 parent 109.656566 0.01880531
+#&gt; 100 parent 110.848485 0.01713257
+#&gt; 101 parent 112.040404 0.01560863
+#&gt; 102 parent 113.232323 0.01422024
+#&gt; 103 parent 114.424242 0.01295535
+#&gt; 104 parent 115.616162 0.01180297
+#&gt; 105 parent 116.808081 0.01075310
+#&gt; 106 parent 118.000000 0.00979661
+#&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: 0x2b30d68&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: 0x2b30d68&gt;
+#&gt;
+#&gt; $hessian_notrans
+#&gt; parent_0 k_parent_sink
+#&gt; parent_0 4.163631 -1203.894
+#&gt; k_parent_sink -1203.893702 1033188.753
+#&gt;
+#&gt; $start
+#&gt; value type
+#&gt; parent_0 98.62 state
+#&gt; k_parent_sink 0.10 deparm
+#&gt;
+#&gt; $start_transformed
+#&gt; value lower upper
+#&gt; parent_0 98.620000 -Inf Inf
+#&gt; log_k_parent_sink -2.302585 -Inf Inf
+#&gt;
+#&gt; $fixed
+#&gt; [1] value type
+#&gt; &lt;0 rows&gt; (or 0-length row.names)
+#&gt;
+#&gt; $data
+#&gt; time variable observed predicted residual
+#&gt; 1 0 parent 98.62 99.17407218 -0.55407218
+#&gt; 2 3 parent 81.43 78.44547872 2.98452128
+#&gt; 3 7 parent 53.18 57.38445742 -4.20445742
+#&gt; 4 14 parent 34.89 33.20400061 1.68599939
+#&gt; 5 30 parent 10.09 9.50814643 0.58185357
+#&gt; 6 62 parent 1.50 0.77966270 0.72033730
+#&gt; 7 90 parent 0.33 0.08739595 0.24260405
+#&gt; 8 118 parent 0.08 0.00979661 0.07020339
+#&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_sink
+#&gt; 99.17407218 0.07815759
+#&gt;
+#&gt; $bparms.fixed
+#&gt; numeric(0)
+#&gt;
+#&gt; $bparms.ode
+#&gt; k_parent_sink
+#&gt; 0.07815759
+#&gt;
+#&gt; $bparms.state
+#&gt; parent
+#&gt; 99.17407
+#&gt;
+#&gt; $date
+#&gt; [1] &quot;Wed Oct 26 23:50:32 2016&quot;
+#&gt;
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mkinfit&quot; &quot;modFit&quot;
+#&gt; </div><div class='input'> <span class='no'>fits</span>[<span class='st'>"SFO"</span>, <span class='st'>"B"</span>, <span class='kw'>drop</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>]</div><div class='output co'>#&gt; [[1]]
+#&gt; $par
+#&gt; parent_0 log_k_parent_sink
+#&gt; 99.174072 -2.549028
+#&gt;
+#&gt; $ssr
+#&gt; [1] 30.65564
+#&gt;
+#&gt; $convergence
+#&gt; [1] 0
+#&gt;
+#&gt; $iterations
+#&gt; [1] 5
+#&gt;
+#&gt; $evaluations
+#&gt; function gradient
+#&gt; 8 15
+#&gt;
+#&gt; $counts
+#&gt; [1] &quot;relative convergence (4)&quot;
+#&gt;
+#&gt; $hessian
+#&gt; parent_0 log_k_parent_sink
+#&gt; parent_0 4.163631 -94.09343
+#&gt; log_k_parent_sink -94.093431 6311.34610
+#&gt;
+#&gt; $residuals
+#&gt; parent parent parent parent parent parent
+#&gt; 0.55407218 -2.98452128 4.20445742 -1.68599939 -0.58185357 -0.72033730
+#&gt; parent parent
+#&gt; -0.24260405 -0.07020339
+#&gt;
+#&gt; $ms
+#&gt; [1] 3.831956
+#&gt;
+#&gt; $var_ms
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $var_ms_unscaled
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $var_ms_unweighted
+#&gt; parent
+#&gt; 3.831956
+#&gt;
+#&gt; $rank
+#&gt; [1] 2
+#&gt;
+#&gt; $df.residual
+#&gt; [1] 6
+#&gt;
+#&gt; $solution_type
+#&gt; [1] &quot;analytical&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] 29
+#&gt;
+#&gt; $time
+#&gt; user system elapsed
+#&gt; 0.068 0.000 0.070
+#&gt;
+#&gt; $mkinmod
+#&gt; &lt;mkinmod&gt; model generated with
+#&gt; Use of formation fractions $use_of_ff: min
+#&gt; Specification $spec:
+#&gt; $parent
+#&gt; $type: SFO; $sink: TRUE
+#&gt; Coefficient matrix $coefmat available
+#&gt;
+#&gt; $observed
+#&gt; name time value
+#&gt; 1 parent 0 98.62
+#&gt; 2 parent 3 81.43
+#&gt; 3 parent 7 53.18
+#&gt; 4 parent 14 34.89
+#&gt; 5 parent 30 10.09
+#&gt; 6 parent 62 1.50
+#&gt; 7 parent 90 0.33
+#&gt; 8 parent 118 0.08
+#&gt;
+#&gt; $obs_vars
+#&gt; [1] &quot;parent&quot;
+#&gt;
+#&gt; $predicted
+#&gt; name time value
+#&gt; 1 parent 0.000000 99.17407218
+#&gt; 2 parent 1.191919 90.35253561
+#&gt; 3 parent 2.383838 82.31567498
+#&gt; 4 parent 3.000000 78.44547872
+#&gt; 5 parent 3.575758 74.99369333
+#&gt; 6 parent 4.767677 68.32300215
+#&gt; 7 parent 5.959596 62.24566915
+#&gt; 8 parent 7.000000 57.38445742
+#&gt; 9 parent 7.151515 56.70891509
+#&gt; 10 parent 8.343434 51.66465547
+#&gt; 11 parent 9.535354 47.06908288
+#&gt; 12 parent 10.727273 42.88228661
+#&gt; 13 parent 11.919192 39.06790599
+#&gt; 14 parent 13.111111 35.59281463
+#&gt; 15 parent 14.000000 33.20400061
+#&gt; 16 parent 14.303030 32.42683275
+#&gt; 17 parent 15.494949 29.54246504
+#&gt; 18 parent 16.686869 26.91466193
+#&gt; 19 parent 17.878788 24.52060198
+#&gt; 20 parent 19.070707 22.33949373
+#&gt; 21 parent 20.262626 20.35239512
+#&gt; 22 parent 21.454545 18.54204899
+#&gt; 23 parent 22.646465 16.89273320
+#&gt; 24 parent 23.838384 15.39012410
+#&gt; 25 parent 25.030303 14.02117212
+#&gt; 26 parent 26.222222 12.77398846
+#&gt; 27 parent 27.414141 11.63774182
+#&gt; 28 parent 28.606061 10.60256435
+#&gt; 29 parent 29.797980 9.65946594
+#&gt; 30 parent 30.000000 9.50814643
+#&gt; 31 parent 30.989899 8.80025617
+#&gt; 32 parent 32.181818 8.01747313
+#&gt; 33 parent 33.373737 7.30431867
+#&gt; 34 parent 34.565657 6.65459931
+#&gt; 35 parent 35.757576 6.06267251
+#&gt; 36 parent 36.949495 5.52339762
+#&gt; 37 parent 38.141414 5.03209124
+#&gt; 38 parent 39.333333 4.58448658
+#&gt; 39 parent 40.525253 4.17669637
+#&gt; 40 parent 41.717172 3.80517911
+#&gt; 41 parent 42.909091 3.46670832
+#&gt; 42 parent 44.101010 3.15834451
+#&gt; 43 parent 45.292929 2.87740968
+#&gt; 44 parent 46.484848 2.62146400
+#&gt; 45 parent 47.676768 2.38828471
+#&gt; 46 parent 48.868687 2.17584671
+#&gt; 47 parent 50.060606 1.98230508
+#&gt; 48 parent 51.252525 1.80597899
+#&gt; 49 parent 52.444444 1.64533711
+#&gt; 50 parent 53.636364 1.49898432
+#&gt; 51 parent 54.828283 1.36564963
+#&gt; 52 parent 56.020202 1.24417505
+#&gt; 53 parent 57.212121 1.13350565
+#&gt; 54 parent 58.404040 1.03268029
+#&gt; 55 parent 59.595960 0.94082335
+#&gt; 56 parent 60.787879 0.85713708
+#&gt; 57 parent 61.979798 0.78089471
+#&gt; 58 parent 62.000000 0.77966270
+#&gt; 59 parent 63.171717 0.71143411
+#&gt; 60 parent 64.363636 0.64815202
+#&gt; 61 parent 65.555556 0.59049888
+#&gt; 62 parent 66.747475 0.53797399
+#&gt; 63 parent 67.939394 0.49012119
+#&gt; 64 parent 69.131313 0.44652489
+#&gt; 65 parent 70.323232 0.40680649
+#&gt; 66 parent 71.515152 0.37062104
+#&gt; 67 parent 72.707071 0.33765429
+#&gt; 68 parent 73.898990 0.30761993
+#&gt; 69 parent 75.090909 0.28025713
+#&gt; 70 parent 76.282828 0.25532825
+#&gt; 71 parent 77.474747 0.23261679
+#&gt; 72 parent 78.666667 0.21192552
+#&gt; 73 parent 79.858586 0.19307474
+#&gt; 74 parent 81.050505 0.17590074
+#&gt; 75 parent 82.242424 0.16025436
+#&gt; 76 parent 83.434343 0.14599973
+#&gt; 77 parent 84.626263 0.13301305
+#&gt; 78 parent 85.818182 0.12118154
+#&gt; 79 parent 87.010101 0.11040244
+#&gt; 80 parent 88.202020 0.10058214
+#&gt; 81 parent 89.393939 0.09163535
+#&gt; 82 parent 90.000000 0.08739595
+#&gt; 83 parent 90.585859 0.08348439
+#&gt; 84 parent 91.777778 0.07605845
+#&gt; 85 parent 92.969697 0.06929305
+#&gt; 86 parent 94.161616 0.06312943
+#&gt; 87 parent 95.353535 0.05751406
+#&gt; 88 parent 96.545455 0.05239819
+#&gt; 89 parent 97.737374 0.04773737
+#&gt; 90 parent 98.929293 0.04349113
+#&gt; 91 parent 100.121212 0.03962259
+#&gt; 92 parent 101.313131 0.03609816
+#&gt; 93 parent 102.505051 0.03288723
+#&gt; 94 parent 103.696970 0.02996191
+#&gt; 95 parent 104.888889 0.02729679
+#&gt; 96 parent 106.080808 0.02486874
+#&gt; 97 parent 107.272727 0.02265667
+#&gt; 98 parent 108.464646 0.02064136
+#&gt; 99 parent 109.656566 0.01880531
+#&gt; 100 parent 110.848485 0.01713257
+#&gt; 101 parent 112.040404 0.01560863
+#&gt; 102 parent 113.232323 0.01422024
+#&gt; 103 parent 114.424242 0.01295535
+#&gt; 104 parent 115.616162 0.01180297
+#&gt; 105 parent 116.808081 0.01075310
+#&gt; 106 parent 118.000000 0.00979661
+#&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: 0x2b30d68&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: 0x2b30d68&gt;
+#&gt;
+#&gt; $hessian_notrans
+#&gt; parent_0 k_parent_sink
+#&gt; parent_0 4.163631 -1203.894
+#&gt; k_parent_sink -1203.893702 1033188.753
+#&gt;
+#&gt; $start
+#&gt; value type
+#&gt; parent_0 98.62 state
+#&gt; k_parent_sink 0.10 deparm
+#&gt;
+#&gt; $start_transformed
+#&gt; value lower upper
+#&gt; parent_0 98.620000 -Inf Inf
+#&gt; log_k_parent_sink -2.302585 -Inf Inf
+#&gt;
+#&gt; $fixed
+#&gt; [1] value type
+#&gt; &lt;0 rows&gt; (or 0-length row.names)
+#&gt;
+#&gt; $data
+#&gt; time variable observed predicted residual
+#&gt; 1 0 parent 98.62 99.17407218 -0.55407218
+#&gt; 2 3 parent 81.43 78.44547872 2.98452128
+#&gt; 3 7 parent 53.18 57.38445742 -4.20445742
+#&gt; 4 14 parent 34.89 33.20400061 1.68599939
+#&gt; 5 30 parent 10.09 9.50814643 0.58185357
+#&gt; 6 62 parent 1.50 0.77966270 0.72033730
+#&gt; 7 90 parent 0.33 0.08739595 0.24260405
+#&gt; 8 118 parent 0.08 0.00979661 0.07020339
+#&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_sink
+#&gt; 99.17407218 0.07815759
+#&gt;
+#&gt; $bparms.fixed
+#&gt; numeric(0)
+#&gt;
+#&gt; $bparms.ode
+#&gt; k_parent_sink
+#&gt; 0.07815759
+#&gt;
+#&gt; $bparms.state
+#&gt; parent
+#&gt; 99.17407
+#&gt;
+#&gt; $date
+#&gt; [1] &quot;Wed Oct 26 23:50:32 2016&quot;
+#&gt;
+#&gt; attr(,&quot;class&quot;)
+#&gt; [1] &quot;mkinfit&quot; &quot;modFit&quot;
+#&gt;
+#&gt; </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="#arguments">Arguments</a></li>
+
+ <li><a href="#value">Value</a></li>
+
+ <li><a href="#examples">Examples</a></li>
+ </ul>
+
+ <h2>Author</h2>
+
+ Johannes Ranke
+
+ </div>
+</div>
+
+ <footer>
+ <div class="copyright">
+ <p>Developed by Johannes Ranke, Eurofins Regulatory AG.</p>
+</div>
+
+<div class="pkgdown">
+ <p>Site built with <a href="http://hadley.github.io/pkgdown/">pkgdown</a>.</p>
+</div>
+
+ </footer>
+ </div>
+
+ </body>
+</html>

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