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| author | Johannes Ranke <jranke@uni-bremen.de> | 2016-10-06 09:19:21 +0200 |
|---|---|---|
| committer | Johannes Ranke <jranke@uni-bremen.de> | 2016-10-06 09:19:21 +0200 |
| commit | 38f9e15f0c972c1516ae737a2bca8d7789581bbd (patch) | |
| tree | 724c9dc19901f24f427757ac81001f07bf298024 /docs/reference/Extract.mmkin.html | |
| parent | ec1487f0f2cef32d44b0c6ce94a6f1b4f65a79d3 (diff) | |
Static documentation rebuilt by pkgdown::build_site()
Diffstat (limited to 'docs/reference/Extract.mmkin.html')
| -rw-r--r-- | docs/reference/Extract.mmkin.html | 1192 |
1 files changed, 1192 insertions, 0 deletions
diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html new file mode 100644 index 00000000..b811eb95 --- /dev/null +++ b/docs/reference/Extract.mmkin.html @@ -0,0 +1,1192 @@ +<!-- 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>[.mmkin. 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/bootswatch/3.3.7/cerulean/bootstrap.min.css" rel="stylesheet" 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="../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"> + <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="../index.html">Home</a> +</li> +<li> + <a href="../reference/index.html">Reference</a> +</li> + </ul> + <ul class="nav navbar-nav navbar-right"> + <li> + <a href="https://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="page-header"> + <h1>Subsetting method for mmkin objects</h1> +</div> + +<div class="row"> + <div class="col-md-9"> + + <p>Subsetting method for mmkin objects.</p> + + + <pre># S3 method for mmkin +[(x, i, j, ..., drop = FALSE)</pre> + + <h2>Arguments</h2> + <dl class="dl-horizontal"> + <dt>x</dt> + <dd>An <code>mmkin 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> + + <div class="Value"> + <h2>Value</h2> + + <p>An object of class <code>mmkin</code>.</p> + </div> + + <h2 id="examples">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'><-</span> <span class='fu'>mmkin</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'>#> dataset +#> model B C +#> FOMC List,42 List,42 +#> attr(,"class") +#> [1] "mmkin" +#> </div><div class='input'> <span class='no'>fits</span>[, <span class='st'>"B"</span>]</div><div class='output co'>#> dataset +#> model B +#> SFO List,42 +#> FOMC List,42 +#> attr(,"class") +#> [1] "mmkin" +#> </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'>#> $par +#> parent_0 log_alpha log_beta +#> 99.666193 2.549849 5.050586 +#> +#> $ssr +#> [1] 28.58291 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 21 +#> +#> $evaluations +#> function gradient +#> 25 78 +#> +#> $counts +#> [1] "both X-convergence and relative convergence (5)" +#> +#> $hessian +#> parent_0 log_alpha log_beta +#> parent_0 4.123033 -95.69983 93.17699 +#> log_alpha -95.699832 6618.85833 -6352.46648 +#> log_beta 93.176993 -6352.46648 6101.23483 +#> +#> $residuals +#> parent parent parent parent parent parent +#> 1.046192647 -3.322396479 3.655156669 -1.705316770 0.406306255 -0.123734689 +#> parent parent +#> -0.036886982 -0.006240458 +#> +#> $ms +#> [1] 3.572863 +#> +#> $var_ms +#> parent +#> 3.572863 +#> +#> $var_ms_unscaled +#> parent +#> 3.572863 +#> +#> $var_ms_unweighted +#> parent +#> 3.572863 +#> +#> $rank +#> [1] 3 +#> +#> $df.residual +#> [1] 5 +#> +#> $solution_type +#> [1] "analytical" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 111 +#> +#> $time +#> user system elapsed +#> 0.256 0.000 0.257 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: min +#> Specification $spec: +#> $parent +#> $type: FOMC; $sink: TRUE +#> +#> $observed +#> name time value +#> 1 parent 0 98.62 +#> 2 parent 3 81.43 +#> 3 parent 7 53.18 +#> 4 parent 14 34.89 +#> 5 parent 30 10.09 +#> 6 parent 62 1.50 +#> 7 parent 90 0.33 +#> 8 parent 118 0.08 +#> +#> $obs_vars +#> [1] "parent" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 99.66619265 +#> 2 parent 1.191919 90.41690342 +#> 3 parent 2.383838 82.08630014 +#> 4 parent 3.000000 78.10760352 +#> 5 parent 3.575758 74.57722848 +#> 6 parent 4.767677 67.80342415 +#> 7 parent 5.959596 61.68822425 +#> 8 parent 7.000000 56.83515667 +#> 9 parent 7.151515 56.16343898 +#> 10 parent 8.343434 51.16836285 +#> 11 parent 9.535354 46.64890734 +#> 12 parent 10.727273 42.55683931 +#> 13 parent 11.919192 38.84911158 +#> 14 parent 13.111111 35.48727414 +#> 15 parent 14.000000 33.18468323 +#> 16 parent 14.303030 32.43695565 +#> 17 parent 15.494949 29.66740651 +#> 18 parent 16.686869 27.15109578 +#> 19 parent 17.878788 24.86335532 +#> 20 parent 19.070707 22.78206538 +#> 21 parent 20.262626 20.88737647 +#> 22 parent 21.454545 19.16146324 +#> 23 parent 22.646465 17.58830644 +#> 24 parent 23.838384 16.15349953 +#> 25 parent 25.030303 14.84407724 +#> 26 parent 26.222222 13.64836315 +#> 27 parent 27.414141 12.55583436 +#> 28 parent 28.606061 11.55700107 +#> 29 parent 29.797980 10.64329940 +#> 30 parent 30.000000 10.49630626 +#> 31 parent 30.989899 9.80699593 +#> 32 parent 32.181818 9.04110261 +#> 33 parent 33.373737 8.33930082 +#> 34 parent 34.565657 7.69587362 +#> 35 parent 35.757576 7.10564515 +#> 36 parent 36.949495 6.56392657 +#> 37 parent 38.141414 6.06646759 +#> 38 parent 39.333333 5.60941311 +#> 39 parent 40.525253 5.18926438 +#> 40 parent 41.717172 4.80284421 +#> 41 parent 42.909091 4.44726569 +#> 42 parent 44.101010 4.11990420 +#> 43 parent 45.292929 3.81837216 +#> 44 parent 46.484848 3.54049644 +#> 45 parent 47.676768 3.28429799 +#> 46 parent 48.868687 3.04797350 +#> 47 parent 50.060606 2.82987892 +#> 48 parent 51.252525 2.62851456 +#> 49 parent 52.444444 2.44251172 +#> 50 parent 53.636364 2.27062056 +#> 51 parent 54.828283 2.11169922 +#> 52 parent 56.020202 1.96470393 +#> 53 parent 57.212121 1.82868009 +#> 54 parent 58.404040 1.70275424 +#> 55 parent 59.595960 1.58612677 +#> 56 parent 60.787879 1.47806529 +#> 57 parent 61.979798 1.37789865 +#> 58 parent 62.000000 1.37626531 +#> 59 parent 63.171717 1.28501157 +#> 60 parent 64.363636 1.19883967 +#> 61 parent 65.555556 1.11886504 +#> 62 parent 66.747475 1.04461220 +#> 63 parent 67.939394 0.97564441 +#> 64 parent 69.131313 0.91156031 +#> 65 parent 70.323232 0.85199096 +#> 66 parent 71.515152 0.79659697 +#> 67 parent 72.707071 0.74506609 +#> 68 parent 73.898990 0.69711084 +#> 69 parent 75.090909 0.65246649 +#> 70 parent 76.282828 0.61088912 +#> 71 parent 77.474747 0.57215389 +#> 72 parent 78.666667 0.53605348 +#> 73 parent 79.858586 0.50239663 +#> 74 parent 81.050505 0.47100683 +#> 75 parent 82.242424 0.44172111 +#> 76 parent 83.434343 0.41438896 +#> 77 parent 84.626263 0.38887128 +#> 78 parent 85.818182 0.36503953 +#> 79 parent 87.010101 0.34277481 +#> 80 parent 88.202020 0.32196716 +#> 81 parent 89.393939 0.30251479 +#> 82 parent 90.000000 0.29311302 +#> 83 parent 90.585859 0.28432347 +#> 84 parent 91.777778 0.26730596 +#> 85 parent 92.969697 0.25138141 +#> 86 parent 94.161616 0.23647487 +#> 87 parent 95.353535 0.22251689 +#> 88 parent 96.545455 0.20944302 +#> 89 parent 97.737374 0.19719349 +#> 90 parent 98.929293 0.18571281 +#> 91 parent 100.121212 0.17494947 +#> 92 parent 101.313131 0.16485560 +#> 93 parent 102.505051 0.15538676 +#> 94 parent 103.696970 0.14650163 +#> 95 parent 104.888889 0.13816179 +#> 96 parent 106.080808 0.13033150 +#> 97 parent 107.272727 0.12297753 +#> 98 parent 108.464646 0.11606895 +#> 99 parent 109.656566 0.10957695 +#> 100 parent 110.848485 0.10347470 +#> 101 parent 112.040404 0.09773723 +#> 102 parent 113.232323 0.09234125 +#> 103 parent 114.424242 0.08726506 +#> 104 parent 115.616162 0.08248842 +#> 105 parent 116.808081 0.07799245 +#> 106 parent 118.000000 0.07375954 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$model < cost.old) { +#> if (!quiet) +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") +#> if (plot) { +#> outtimes_plot = seq(min(observed$time), max(observed$time), +#> length.out = 100) +#> out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, +#> solution_type = solution_type, use_compiled = use_compiled, +#> method.ode = method.ode, atol = atol, rtol = rtol, +#> ...) +#> plot(0, type = "n", xlim = range(observed$time), +#> ylim = c(0, max(observed$value, na.rm = TRUE)), +#> xlab = "Time", ylab = "Observed") +#> col_obs <- pch_obs <- 1:length(obs_vars) +#> lty_obs <- rep(1, length(obs_vars)) +#> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars +#> for (obs_var in obs_vars) { +#> points(subset(observed, name == obs_var, c(time, +#> value)), pch = pch_obs[obs_var], col = col_obs[obs_var]) +#> } +#> matlines(out_plot$time, out_plot[-1], col = col_obs, +#> lty = lty_obs) +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) +#> } +#> assign("cost.old", mC$model, inherits = TRUE) +#> } +#> return(mC) +#> } +#> <environment: 0x27fc328> +#> +#> $cost_notrans +#> function (P) +#> { +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> parms.fixed) +#> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> return(mC) +#> } +#> <environment: 0x27fc328> +#> +#> $hessian_notrans +#> parent_0 alpha beta +#> parent_0 4.1230329 -7.473531 0.5968527 +#> alpha -7.4735307 40.365690 -3.1777189 +#> beta 0.5968527 -3.177719 0.2503425 +#> +#> $start +#> value type +#> parent_0 98.62 state +#> alpha 1.00 deparm +#> beta 10.00 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 98.620000 -Inf Inf +#> log_alpha 0.000000 -Inf Inf +#> log_beta 2.302585 -Inf Inf +#> +#> $fixed +#> [1] value type +#> <0 rows> (or 0-length row.names) +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 98.62 99.66619265 -1.046192647 +#> 2 3 parent 81.43 78.10760352 3.322396479 +#> 3 7 parent 53.18 56.83515667 -3.655156669 +#> 4 14 parent 34.89 33.18468323 1.705316770 +#> 5 30 parent 10.09 10.49630626 -0.406306255 +#> 6 62 parent 1.50 1.37626531 0.123734689 +#> 7 90 parent 0.33 0.29311302 0.036886982 +#> 8 118 parent 0.08 0.07375954 0.006240458 +#> +#> $atol +#> [1] 1e-08 +#> +#> $rtol +#> [1] 1e-10 +#> +#> $weight.ini +#> [1] "none" +#> +#> $reweight.tol +#> [1] 1e-08 +#> +#> $reweight.max.iter +#> [1] 10 +#> +#> $bparms.optim +#> parent_0 alpha beta +#> 99.66619 12.80517 156.11390 +#> +#> $bparms.fixed +#> numeric(0) +#> +#> $bparms.ode +#> alpha beta +#> 12.80517 156.11390 +#> +#> $bparms.state +#> parent +#> 99.66619 +#> +#> $date +#> [1] "Thu Oct 6 09:17:52 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit" +#> </div><div class='input'> <span class='no'>fits</span>[<span class='st'>"SFO"</span>, <span class='st'>"B"</span>]</div><div class='output co'>#> dataset +#> model B +#> SFO List,42 +#> attr(,"class") +#> [1] "mmkin" +#> </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'>#> $par +#> parent_0 log_k_parent_sink +#> 99.174072 -2.549028 +#> +#> $ssr +#> [1] 30.65564 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 5 +#> +#> $evaluations +#> function gradient +#> 8 15 +#> +#> $counts +#> [1] "relative convergence (4)" +#> +#> $hessian +#> parent_0 log_k_parent_sink +#> parent_0 4.163631 -94.09343 +#> log_k_parent_sink -94.093431 6311.34610 +#> +#> $residuals +#> parent parent parent parent parent parent +#> 0.55407218 -2.98452128 4.20445742 -1.68599939 -0.58185357 -0.72033730 +#> parent parent +#> -0.24260405 -0.07020339 +#> +#> $ms +#> [1] 3.831956 +#> +#> $var_ms +#> parent +#> 3.831956 +#> +#> $var_ms_unscaled +#> parent +#> 3.831956 +#> +#> $var_ms_unweighted +#> parent +#> 3.831956 +#> +#> $rank +#> [1] 2 +#> +#> $df.residual +#> [1] 6 +#> +#> $solution_type +#> [1] "analytical" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 29 +#> +#> $time +#> user system elapsed +#> 0.068 0.000 0.068 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: min +#> Specification $spec: +#> $parent +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> +#> $observed +#> name time value +#> 1 parent 0 98.62 +#> 2 parent 3 81.43 +#> 3 parent 7 53.18 +#> 4 parent 14 34.89 +#> 5 parent 30 10.09 +#> 6 parent 62 1.50 +#> 7 parent 90 0.33 +#> 8 parent 118 0.08 +#> +#> $obs_vars +#> [1] "parent" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 99.17407218 +#> 2 parent 1.191919 90.35253561 +#> 3 parent 2.383838 82.31567498 +#> 4 parent 3.000000 78.44547872 +#> 5 parent 3.575758 74.99369333 +#> 6 parent 4.767677 68.32300215 +#> 7 parent 5.959596 62.24566915 +#> 8 parent 7.000000 57.38445742 +#> 9 parent 7.151515 56.70891509 +#> 10 parent 8.343434 51.66465547 +#> 11 parent 9.535354 47.06908288 +#> 12 parent 10.727273 42.88228661 +#> 13 parent 11.919192 39.06790599 +#> 14 parent 13.111111 35.59281463 +#> 15 parent 14.000000 33.20400061 +#> 16 parent 14.303030 32.42683275 +#> 17 parent 15.494949 29.54246504 +#> 18 parent 16.686869 26.91466193 +#> 19 parent 17.878788 24.52060198 +#> 20 parent 19.070707 22.33949373 +#> 21 parent 20.262626 20.35239512 +#> 22 parent 21.454545 18.54204899 +#> 23 parent 22.646465 16.89273320 +#> 24 parent 23.838384 15.39012410 +#> 25 parent 25.030303 14.02117212 +#> 26 parent 26.222222 12.77398846 +#> 27 parent 27.414141 11.63774182 +#> 28 parent 28.606061 10.60256435 +#> 29 parent 29.797980 9.65946594 +#> 30 parent 30.000000 9.50814643 +#> 31 parent 30.989899 8.80025617 +#> 32 parent 32.181818 8.01747313 +#> 33 parent 33.373737 7.30431867 +#> 34 parent 34.565657 6.65459931 +#> 35 parent 35.757576 6.06267251 +#> 36 parent 36.949495 5.52339762 +#> 37 parent 38.141414 5.03209124 +#> 38 parent 39.333333 4.58448658 +#> 39 parent 40.525253 4.17669637 +#> 40 parent 41.717172 3.80517911 +#> 41 parent 42.909091 3.46670832 +#> 42 parent 44.101010 3.15834451 +#> 43 parent 45.292929 2.87740968 +#> 44 parent 46.484848 2.62146400 +#> 45 parent 47.676768 2.38828471 +#> 46 parent 48.868687 2.17584671 +#> 47 parent 50.060606 1.98230508 +#> 48 parent 51.252525 1.80597899 +#> 49 parent 52.444444 1.64533711 +#> 50 parent 53.636364 1.49898432 +#> 51 parent 54.828283 1.36564963 +#> 52 parent 56.020202 1.24417505 +#> 53 parent 57.212121 1.13350565 +#> 54 parent 58.404040 1.03268029 +#> 55 parent 59.595960 0.94082335 +#> 56 parent 60.787879 0.85713708 +#> 57 parent 61.979798 0.78089471 +#> 58 parent 62.000000 0.77966270 +#> 59 parent 63.171717 0.71143411 +#> 60 parent 64.363636 0.64815202 +#> 61 parent 65.555556 0.59049888 +#> 62 parent 66.747475 0.53797399 +#> 63 parent 67.939394 0.49012119 +#> 64 parent 69.131313 0.44652489 +#> 65 parent 70.323232 0.40680649 +#> 66 parent 71.515152 0.37062104 +#> 67 parent 72.707071 0.33765429 +#> 68 parent 73.898990 0.30761993 +#> 69 parent 75.090909 0.28025713 +#> 70 parent 76.282828 0.25532825 +#> 71 parent 77.474747 0.23261679 +#> 72 parent 78.666667 0.21192552 +#> 73 parent 79.858586 0.19307474 +#> 74 parent 81.050505 0.17590074 +#> 75 parent 82.242424 0.16025436 +#> 76 parent 83.434343 0.14599973 +#> 77 parent 84.626263 0.13301305 +#> 78 parent 85.818182 0.12118154 +#> 79 parent 87.010101 0.11040244 +#> 80 parent 88.202020 0.10058214 +#> 81 parent 89.393939 0.09163535 +#> 82 parent 90.000000 0.08739595 +#> 83 parent 90.585859 0.08348439 +#> 84 parent 91.777778 0.07605845 +#> 85 parent 92.969697 0.06929305 +#> 86 parent 94.161616 0.06312943 +#> 87 parent 95.353535 0.05751406 +#> 88 parent 96.545455 0.05239819 +#> 89 parent 97.737374 0.04773737 +#> 90 parent 98.929293 0.04349113 +#> 91 parent 100.121212 0.03962259 +#> 92 parent 101.313131 0.03609816 +#> 93 parent 102.505051 0.03288723 +#> 94 parent 103.696970 0.02996191 +#> 95 parent 104.888889 0.02729679 +#> 96 parent 106.080808 0.02486874 +#> 97 parent 107.272727 0.02265667 +#> 98 parent 108.464646 0.02064136 +#> 99 parent 109.656566 0.01880531 +#> 100 parent 110.848485 0.01713257 +#> 101 parent 112.040404 0.01560863 +#> 102 parent 113.232323 0.01422024 +#> 103 parent 114.424242 0.01295535 +#> 104 parent 115.616162 0.01180297 +#> 105 parent 116.808081 0.01075310 +#> 106 parent 118.000000 0.00979661 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$model < cost.old) { +#> if (!quiet) +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") +#> if (plot) { +#> outtimes_plot = seq(min(observed$time), max(observed$time), +#> length.out = 100) +#> out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, +#> solution_type = solution_type, use_compiled = use_compiled, +#> method.ode = method.ode, atol = atol, rtol = rtol, +#> ...) +#> plot(0, type = "n", xlim = range(observed$time), +#> ylim = c(0, max(observed$value, na.rm = TRUE)), +#> xlab = "Time", ylab = "Observed") +#> col_obs <- pch_obs <- 1:length(obs_vars) +#> lty_obs <- rep(1, length(obs_vars)) +#> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars +#> for (obs_var in obs_vars) { +#> points(subset(observed, name == obs_var, c(time, +#> value)), pch = pch_obs[obs_var], col = col_obs[obs_var]) +#> } +#> matlines(out_plot$time, out_plot[-1], col = col_obs, +#> lty = lty_obs) +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) +#> } +#> assign("cost.old", mC$model, inherits = TRUE) +#> } +#> return(mC) +#> } +#> <environment: 0x2e966b0> +#> +#> $cost_notrans +#> function (P) +#> { +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> parms.fixed) +#> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> return(mC) +#> } +#> <environment: 0x2e966b0> +#> +#> $hessian_notrans +#> parent_0 k_parent_sink +#> parent_0 4.163631 -1203.894 +#> k_parent_sink -1203.893702 1033188.753 +#> +#> $start +#> value type +#> parent_0 98.62 state +#> k_parent_sink 0.10 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 98.620000 -Inf Inf +#> log_k_parent_sink -2.302585 -Inf Inf +#> +#> $fixed +#> [1] value type +#> <0 rows> (or 0-length row.names) +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 98.62 99.17407218 -0.55407218 +#> 2 3 parent 81.43 78.44547872 2.98452128 +#> 3 7 parent 53.18 57.38445742 -4.20445742 +#> 4 14 parent 34.89 33.20400061 1.68599939 +#> 5 30 parent 10.09 9.50814643 0.58185357 +#> 6 62 parent 1.50 0.77966270 0.72033730 +#> 7 90 parent 0.33 0.08739595 0.24260405 +#> 8 118 parent 0.08 0.00979661 0.07020339 +#> +#> $atol +#> [1] 1e-08 +#> +#> $rtol +#> [1] 1e-10 +#> +#> $weight.ini +#> [1] "none" +#> +#> $reweight.tol +#> [1] 1e-08 +#> +#> $reweight.max.iter +#> [1] 10 +#> +#> $bparms.optim +#> parent_0 k_parent_sink +#> 99.17407218 0.07815759 +#> +#> $bparms.fixed +#> numeric(0) +#> +#> $bparms.ode +#> k_parent_sink +#> 0.07815759 +#> +#> $bparms.state +#> parent +#> 99.17407 +#> +#> $date +#> [1] "Thu Oct 6 09:17:51 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit" +#> </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'>#> [[1]] +#> $par +#> parent_0 log_k_parent_sink +#> 99.174072 -2.549028 +#> +#> $ssr +#> [1] 30.65564 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 5 +#> +#> $evaluations +#> function gradient +#> 8 15 +#> +#> $counts +#> [1] "relative convergence (4)" +#> +#> $hessian +#> parent_0 log_k_parent_sink +#> parent_0 4.163631 -94.09343 +#> log_k_parent_sink -94.093431 6311.34610 +#> +#> $residuals +#> parent parent parent parent parent parent +#> 0.55407218 -2.98452128 4.20445742 -1.68599939 -0.58185357 -0.72033730 +#> parent parent +#> -0.24260405 -0.07020339 +#> +#> $ms +#> [1] 3.831956 +#> +#> $var_ms +#> parent +#> 3.831956 +#> +#> $var_ms_unscaled +#> parent +#> 3.831956 +#> +#> $var_ms_unweighted +#> parent +#> 3.831956 +#> +#> $rank +#> [1] 2 +#> +#> $df.residual +#> [1] 6 +#> +#> $solution_type +#> [1] "analytical" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 29 +#> +#> $time +#> user system elapsed +#> 0.068 0.000 0.068 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: min +#> Specification $spec: +#> $parent +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> +#> $observed +#> name time value +#> 1 parent 0 98.62 +#> 2 parent 3 81.43 +#> 3 parent 7 53.18 +#> 4 parent 14 34.89 +#> 5 parent 30 10.09 +#> 6 parent 62 1.50 +#> 7 parent 90 0.33 +#> 8 parent 118 0.08 +#> +#> $obs_vars +#> [1] "parent" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 99.17407218 +#> 2 parent 1.191919 90.35253561 +#> 3 parent 2.383838 82.31567498 +#> 4 parent 3.000000 78.44547872 +#> 5 parent 3.575758 74.99369333 +#> 6 parent 4.767677 68.32300215 +#> 7 parent 5.959596 62.24566915 +#> 8 parent 7.000000 57.38445742 +#> 9 parent 7.151515 56.70891509 +#> 10 parent 8.343434 51.66465547 +#> 11 parent 9.535354 47.06908288 +#> 12 parent 10.727273 42.88228661 +#> 13 parent 11.919192 39.06790599 +#> 14 parent 13.111111 35.59281463 +#> 15 parent 14.000000 33.20400061 +#> 16 parent 14.303030 32.42683275 +#> 17 parent 15.494949 29.54246504 +#> 18 parent 16.686869 26.91466193 +#> 19 parent 17.878788 24.52060198 +#> 20 parent 19.070707 22.33949373 +#> 21 parent 20.262626 20.35239512 +#> 22 parent 21.454545 18.54204899 +#> 23 parent 22.646465 16.89273320 +#> 24 parent 23.838384 15.39012410 +#> 25 parent 25.030303 14.02117212 +#> 26 parent 26.222222 12.77398846 +#> 27 parent 27.414141 11.63774182 +#> 28 parent 28.606061 10.60256435 +#> 29 parent 29.797980 9.65946594 +#> 30 parent 30.000000 9.50814643 +#> 31 parent 30.989899 8.80025617 +#> 32 parent 32.181818 8.01747313 +#> 33 parent 33.373737 7.30431867 +#> 34 parent 34.565657 6.65459931 +#> 35 parent 35.757576 6.06267251 +#> 36 parent 36.949495 5.52339762 +#> 37 parent 38.141414 5.03209124 +#> 38 parent 39.333333 4.58448658 +#> 39 parent 40.525253 4.17669637 +#> 40 parent 41.717172 3.80517911 +#> 41 parent 42.909091 3.46670832 +#> 42 parent 44.101010 3.15834451 +#> 43 parent 45.292929 2.87740968 +#> 44 parent 46.484848 2.62146400 +#> 45 parent 47.676768 2.38828471 +#> 46 parent 48.868687 2.17584671 +#> 47 parent 50.060606 1.98230508 +#> 48 parent 51.252525 1.80597899 +#> 49 parent 52.444444 1.64533711 +#> 50 parent 53.636364 1.49898432 +#> 51 parent 54.828283 1.36564963 +#> 52 parent 56.020202 1.24417505 +#> 53 parent 57.212121 1.13350565 +#> 54 parent 58.404040 1.03268029 +#> 55 parent 59.595960 0.94082335 +#> 56 parent 60.787879 0.85713708 +#> 57 parent 61.979798 0.78089471 +#> 58 parent 62.000000 0.77966270 +#> 59 parent 63.171717 0.71143411 +#> 60 parent 64.363636 0.64815202 +#> 61 parent 65.555556 0.59049888 +#> 62 parent 66.747475 0.53797399 +#> 63 parent 67.939394 0.49012119 +#> 64 parent 69.131313 0.44652489 +#> 65 parent 70.323232 0.40680649 +#> 66 parent 71.515152 0.37062104 +#> 67 parent 72.707071 0.33765429 +#> 68 parent 73.898990 0.30761993 +#> 69 parent 75.090909 0.28025713 +#> 70 parent 76.282828 0.25532825 +#> 71 parent 77.474747 0.23261679 +#> 72 parent 78.666667 0.21192552 +#> 73 parent 79.858586 0.19307474 +#> 74 parent 81.050505 0.17590074 +#> 75 parent 82.242424 0.16025436 +#> 76 parent 83.434343 0.14599973 +#> 77 parent 84.626263 0.13301305 +#> 78 parent 85.818182 0.12118154 +#> 79 parent 87.010101 0.11040244 +#> 80 parent 88.202020 0.10058214 +#> 81 parent 89.393939 0.09163535 +#> 82 parent 90.000000 0.08739595 +#> 83 parent 90.585859 0.08348439 +#> 84 parent 91.777778 0.07605845 +#> 85 parent 92.969697 0.06929305 +#> 86 parent 94.161616 0.06312943 +#> 87 parent 95.353535 0.05751406 +#> 88 parent 96.545455 0.05239819 +#> 89 parent 97.737374 0.04773737 +#> 90 parent 98.929293 0.04349113 +#> 91 parent 100.121212 0.03962259 +#> 92 parent 101.313131 0.03609816 +#> 93 parent 102.505051 0.03288723 +#> 94 parent 103.696970 0.02996191 +#> 95 parent 104.888889 0.02729679 +#> 96 parent 106.080808 0.02486874 +#> 97 parent 107.272727 0.02265667 +#> 98 parent 108.464646 0.02064136 +#> 99 parent 109.656566 0.01880531 +#> 100 parent 110.848485 0.01713257 +#> 101 parent 112.040404 0.01560863 +#> 102 parent 113.232323 0.01422024 +#> 103 parent 114.424242 0.01295535 +#> 104 parent 115.616162 0.01180297 +#> 105 parent 116.808081 0.01075310 +#> 106 parent 118.000000 0.00979661 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$model < cost.old) { +#> if (!quiet) +#> cat("Model cost at call ", calls, ": ", mC$model, +#> "\n") +#> if (plot) { +#> outtimes_plot = seq(min(observed$time), max(observed$time), +#> length.out = 100) +#> out_plot <- mkinpredict(mkinmod, parms, odeini, outtimes_plot, +#> solution_type = solution_type, use_compiled = use_compiled, +#> method.ode = method.ode, atol = atol, rtol = rtol, +#> ...) +#> plot(0, type = "n", xlim = range(observed$time), +#> ylim = c(0, max(observed$value, na.rm = TRUE)), +#> xlab = "Time", ylab = "Observed") +#> col_obs <- pch_obs <- 1:length(obs_vars) +#> lty_obs <- rep(1, length(obs_vars)) +#> names(col_obs) <- names(pch_obs) <- names(lty_obs) <- obs_vars +#> for (obs_var in obs_vars) { +#> points(subset(observed, name == obs_var, c(time, +#> value)), pch = pch_obs[obs_var], col = col_obs[obs_var]) +#> } +#> matlines(out_plot$time, out_plot[-1], col = col_obs, +#> lty = lty_obs) +#> legend("topright", inset = c(0.05, 0.05), legend = obs_vars, +#> col = col_obs, pch = pch_obs, lty = 1:length(pch_obs)) +#> } +#> assign("cost.old", mC$model, inherits = TRUE) +#> } +#> return(mC) +#> } +#> <environment: 0x2e966b0> +#> +#> $cost_notrans +#> function (P) +#> { +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> parms.fixed) +#> out <- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> return(mC) +#> } +#> <environment: 0x2e966b0> +#> +#> $hessian_notrans +#> parent_0 k_parent_sink +#> parent_0 4.163631 -1203.894 +#> k_parent_sink -1203.893702 1033188.753 +#> +#> $start +#> value type +#> parent_0 98.62 state +#> k_parent_sink 0.10 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 98.620000 -Inf Inf +#> log_k_parent_sink -2.302585 -Inf Inf +#> +#> $fixed +#> [1] value type +#> <0 rows> (or 0-length row.names) +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 98.62 99.17407218 -0.55407218 +#> 2 3 parent 81.43 78.44547872 2.98452128 +#> 3 7 parent 53.18 57.38445742 -4.20445742 +#> 4 14 parent 34.89 33.20400061 1.68599939 +#> 5 30 parent 10.09 9.50814643 0.58185357 +#> 6 62 parent 1.50 0.77966270 0.72033730 +#> 7 90 parent 0.33 0.08739595 0.24260405 +#> 8 118 parent 0.08 0.00979661 0.07020339 +#> +#> $atol +#> [1] 1e-08 +#> +#> $rtol +#> [1] 1e-10 +#> +#> $weight.ini +#> [1] "none" +#> +#> $reweight.tol +#> [1] 1e-08 +#> +#> $reweight.max.iter +#> [1] 10 +#> +#> $bparms.optim +#> parent_0 k_parent_sink +#> 99.17407218 0.07815759 +#> +#> $bparms.fixed +#> numeric(0) +#> +#> $bparms.ode +#> k_parent_sink +#> 0.07815759 +#> +#> $bparms.state +#> parent +#> 99.17407 +#> +#> $date +#> [1] "Thu Oct 6 09:17:51 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit" +#> +#> </div></pre> + </div> + <div class="col-md-3"> + <h2>Author</h2> + + Johannes Ranke + + </div> +</div> + + <footer> + <p>Built by <a href="http://hadley.github.io/pkgdown/">pkgdown</a>. Styled with <a href="http://getbootstrap.com">Bootstrap 3</a>.</p> + </footer> + </div> + + </body> +</html> |