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<h1>Three experimental datasets from two water sediment systems and one soil</h1>
</div>
<p>The datasets were used for the comparative validation of several kinetic evaluation
software packages (Ranke, 2014).</p>
<pre class="usage"><span class='no'>test_data_from_UBA_2014</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A list containing three datasets as an R6 class defined by <code><a href='mkinds.html'>mkinds</a></code>.
Each dataset has, among others, the following components</p><dl class='dl-horizontal'>
<dt><code>title</code></dt><dd><p>The name of the dataset, e.g. <code>UBA_2014_WS_river</code></p></dd>
<dt><code>data</code></dt><dd><p>A data frame with the data in the form expected by <code><a href='mkinfit.html'>mkinfit</a></code></p></dd>
</dl>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative
zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'>
<span class='co'># This is a level P-II evaluation of the dataset according to the FOCUS kinetics</span>
<span class='co'># guidance. Due to the strong correlation of the parameter estimates, the</span>
<span class='co'># covariance matrix is not returned. Note that level P-II evaluations are</span>
<span class='co'># generally considered deprecated due to the frequent occurrence of such</span>
<span class='co'># large parameter correlations, among other reasons (e.g. the adequacy of the</span>
<span class='co'># model).</span>
<span class='no'>m_ws</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent_w</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"parent_s"</span>),
<span class='kw'>parent_s</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"parent_w"</span>))</div><div class='output co'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'> <span class='no'>f_river</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_ws</span>, <span class='no'>test_data_from_UBA_2014</span><span class='kw'>[[</span><span class='fl'>1</span>]]$<span class='no'>data</span>)</div><div class='output co'>#> Model cost at call 1 : 2371.755
#> Model cost at call 3 : 2371.755
#> Model cost at call 7 : 457.5705
#> Model cost at call 10 : 457.5608
#> Model cost at call 14 : 297.2882
#> Model cost at call 16 : 297.2882
#> Model cost at call 18 : 297.2881
#> Model cost at call 21 : 275.6034
#> Model cost at call 23 : 275.6034
#> Model cost at call 27 : 268.2102
#> Model cost at call 29 : 268.2101
#> Model cost at call 33 : 255.941
#> Model cost at call 35 : 255.941
#> Model cost at call 39 : 246.486
#> Model cost at call 41 : 246.486
#> Model cost at call 45 : 231.4275
#> Model cost at call 47 : 231.4275
#> Model cost at call 51 : 212.4338
#> Model cost at call 52 : 212.4338
#> Model cost at call 53 : 212.4337
#> Model cost at call 57 : 203.7185
#> Model cost at call 58 : 203.7185
#> Model cost at call 63 : 198.3304
#> Model cost at call 69 : 198.3304
#> Model cost at call 70 : 195.794
#> Model cost at call 72 : 195.7939
#> Model cost at call 76 : 195.2477
#> Model cost at call 77 : 195.2477
#> Model cost at call 82 : 191.6184
#> Model cost at call 84 : 191.6184
#> Model cost at call 88 : 189.9011
#> Model cost at call 90 : 189.9011
#> Model cost at call 91 : 189.9011
#> Model cost at call 94 : 189.223
#> Model cost at call 95 : 189.223
#> Model cost at call 100 : 188.8728
#> Model cost at call 101 : 188.8728
#> Model cost at call 103 : 188.8728
#> Model cost at call 106 : 188.2057
#> Model cost at call 107 : 188.2057
#> Model cost at call 112 : 187.8429
#> Model cost at call 118 : 187.6219
#> Model cost at call 119 : 187.3931
#> Model cost at call 121 : 187.3931
#> Model cost at call 125 : 187.1236
#> Model cost at call 126 : 187.1236
#> Model cost at call 131 : 186.9995
#> Model cost at call 137 : 186.927
#> Model cost at call 139 : 186.927
#> Model cost at call 143 : 186.8909
#> Model cost at call 146 : 186.8909
#> Model cost at call 150 : 186.8708
#> Model cost at call 152 : 186.8708
#> Model cost at call 157 : 186.8606
#> Model cost at call 159 : 186.8606
#> Model cost at call 161 : 186.8606
#> Model cost at call 162 : 186.8606
#> Model cost at call 167 : 186.8551
#> Model cost at call 169 : 186.8551
#> Model cost at call 176 : 186.8519
#> Model cost at call 177 : 186.8519
#> Model cost at call 180 : 186.8519
#> Model cost at call 181 : 186.8519
#> Model cost at call 186 : 186.8504
#> Model cost at call 187 : 186.8504
#> Model cost at call 196 : 186.8496
#> Model cost at call 197 : 186.8496
#> Model cost at call 200 : 186.8496
#> Model cost at call 206 : 186.8493
#> Model cost at call 211 : 186.8493
#> Model cost at call 215 : 186.8493
#> Model cost at call 216 : 186.8491
#> Model cost at call 225 : 186.8491
#> Model cost at call 226 : 186.849
#> Model cost at call 236 : 186.8489
#> Model cost at call 246 : 186.8489
#> Model cost at call 254 : 186.8489
#> Model cost at call 257 : 186.8489
#> Model cost at call 265 : 186.8489
#> Model cost at call 268 : 186.8489
#> Model cost at call 276 : 186.8489
#> Model cost at call 279 : 186.8489
#> Model cost at call 287 : 186.8489
#> Model cost at call 290 : 186.8489
#> Model cost at call 298 : 186.8489
#> Model cost at call 301 : 186.8489
#> Model cost at call 309 : 186.8489
#> Model cost at call 312 : 186.8489
#> Model cost at call 320 : 186.8489
#> Model cost at call 323 : 186.8489
#> Model cost at call 331 : 186.8489
#> Model cost at call 334 : 186.8489
#> Model cost at call 342 : 186.8489
#> Model cost at call 345 : 186.8489
#> Model cost at call 353 : 186.8489
#> Model cost at call 356 : 186.8489
#> Model cost at call 367 : 186.8489
#> Model cost at call 374 : 186.8489
#> Model cost at call 375 : 186.8489
#> Model cost at call 380 : 186.8489
#> Model cost at call 382 : 186.8489
#> Model cost at call 383 : 186.8489
#> Optimisation by method Port successfully terminated.</div><div class='input'> <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>f_river</span>)</div><img src='test_data_from_UBA_2014-6.png' alt='' width='540' height='400' /><div class='input'>
<span class='fu'>summary</span>(<span class='no'>f_river</span>)$<span class='no'>bpar</span></div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower
#> parent_w_0 9.598567e+01 2.33959810 4.102657e+01 9.568973e-19 NA
#> k_parent_w_sink 3.603743e-01 0.03497716 1.030313e+01 4.988281e-09 NA
#> k_parent_w_parent_s 6.031370e-02 0.01746026 3.454342e+00 1.514738e-03 NA
#> k_parent_s_sink 5.099834e-11 0.10381939 4.912217e-10 5.000000e-01 NA
#> k_parent_s_parent_w 7.419672e-02 0.11338174 6.543974e-01 2.608057e-01 NA
#> Upper
#> parent_w_0 NA
#> k_parent_w_sink NA
#> k_parent_w_parent_s NA
#> k_parent_s_sink NA
#> k_parent_s_parent_w NA</div><div class='input'> <span class='fu'><a href='mkinerrmin.html'>mkinerrmin</a></span>(<span class='no'>f_river</span>)</div><div class='output co'>#> err.min n.optim df
#> All data 0.09246946 5 6
#> parent_w 0.06377096 3 3
#> parent_s 0.20882324 2 3</div><div class='input'>
<span class='co'># This is the evaluation used for the validation of software packages</span>
<span class='co'># in the expertise from 2014</span>
<span class='no'>m_soil</span> <span class='kw'><-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>parent</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='fu'>c</span>(<span class='st'>"M1"</span>, <span class='st'>"M2"</span>)),
<span class='kw'>M1</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"M3"</span>),
<span class='kw'>M2</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></span>(<span class='st'>"SFO"</span>, <span class='st'>"M3"</span>),
<span class='kw'>M3</span> <span class='kw'>=</span> <span class='fu'><a href='mkinsub.html'>mkinsub</a></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'>#> <span class='message'>Successfully compiled differential equation model from auto-generated C code.</span></div><div class='input'>
<span class='no'>f_soil</span> <span class='kw'><-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>m_soil</span>, <span class='no'>test_data_from_UBA_2014</span><span class='kw'>[[</span><span class='fl'>3</span>]]$<span class='no'>data</span>)</div><div class='output co'>#> Model cost at call 1 : 340.115
#> Model cost at call 3 : 340.115
#> Model cost at call 12 : 278.5521
#> Model cost at call 14 : 278.5499
#> Model cost at call 22 : 244.4153
#> Model cost at call 24 : 244.4152
#> Model cost at call 32 : 211.0249
#> Model cost at call 34 : 211.0247
#> Model cost at call 42 : 151.2576
#> Model cost at call 44 : 151.2575
#> Model cost at call 46 : 151.2574
#> Model cost at call 52 : 109.7633
#> Model cost at call 53 : 100.8415
#> Model cost at call 58 : 100.8412
#> Model cost at call 61 : 100.8412
#> Model cost at call 62 : 100.8411
#> Model cost at call 64 : 70.07576
#> Model cost at call 66 : 70.07568
#> Model cost at call 76 : 64.29488
#> Model cost at call 78 : 64.29487
#> Model cost at call 86 : 61.39756
#> Model cost at call 88 : 61.39755
#> Model cost at call 96 : 57.47933
#> Model cost at call 98 : 57.47932
#> Model cost at call 106 : 52.46647
#> Model cost at call 108 : 52.46646
#> Model cost at call 116 : 48.17301
#> Model cost at call 118 : 48.173
#> Model cost at call 126 : 45.15666
#> Model cost at call 128 : 45.15665
#> Model cost at call 137 : 44.55574
#> Model cost at call 139 : 44.55573
#> Model cost at call 143 : 44.55573
#> Model cost at call 147 : 43.13847
#> Model cost at call 149 : 43.13847
#> Model cost at call 151 : 43.13847
#> Model cost at call 158 : 43.11922
#> Model cost at call 160 : 43.11922
#> Model cost at call 168 : 42.29535
#> Model cost at call 170 : 42.29535
#> Model cost at call 178 : 42.03979
#> Model cost at call 180 : 42.03979
#> Model cost at call 189 : 41.56286
#> Model cost at call 190 : 41.12187
#> Model cost at call 191 : 39.73019
#> Model cost at call 192 : 39.31762
#> Model cost at call 193 : 39.31762
#> Model cost at call 196 : 39.31762
#> Model cost at call 203 : 38.6346
#> Model cost at call 204 : 38.6346
#> Model cost at call 205 : 38.63459
#> Model cost at call 209 : 38.63459
#> Model cost at call 210 : 38.63459
#> Model cost at call 211 : 38.63459
#> Model cost at call 213 : 38.12767
#> Model cost at call 215 : 38.12767
#> Model cost at call 223 : 38.04349
#> Model cost at call 225 : 38.04349
#> Model cost at call 229 : 38.04349
#> Model cost at call 233 : 37.93963
#> Model cost at call 236 : 37.93963
#> Model cost at call 243 : 37.87645
#> Model cost at call 244 : 37.87645
#> Model cost at call 254 : 37.79144
#> Model cost at call 256 : 37.79144
#> Model cost at call 264 : 37.7493
#> Model cost at call 269 : 37.7493
#> Model cost at call 274 : 37.72466
#> Model cost at call 275 : 37.72466
#> Model cost at call 279 : 37.72466
#> Model cost at call 283 : 37.72466
#> Model cost at call 284 : 37.71402
#> Model cost at call 285 : 37.71402
#> Model cost at call 287 : 37.71402
#> Model cost at call 294 : 37.70366
#> Model cost at call 295 : 37.70366
#> Model cost at call 296 : 37.70366
#> Model cost at call 305 : 37.69553
#> Model cost at call 306 : 37.69553
#> Model cost at call 307 : 37.69553
#> Model cost at call 315 : 37.6936
#> Model cost at call 319 : 37.6936
#> Model cost at call 321 : 37.6936
#> Model cost at call 326 : 37.6924
#> Model cost at call 328 : 37.6924
#> Model cost at call 329 : 37.6924
#> Model cost at call 336 : 37.69198
#> Model cost at call 338 : 37.69198
#> Model cost at call 344 : 37.69198
#> Model cost at call 348 : 37.69197
#> Model cost at call 350 : 37.69197
#> Model cost at call 363 : 37.69197
#> Model cost at call 364 : 37.69197
#> Model cost at call 367 : 37.69197
#> Model cost at call 382 : 37.69197
#> Model cost at call 384 : 37.69197
#> Model cost at call 387 : 37.69197
#> Model cost at call 401 : 37.69197
#> Model cost at call 420 : 37.69197
#> Model cost at call 441 : 37.69197
#> Optimisation by method Port successfully terminated.</div><div class='input'> <span class='fu'><a href='plot.mkinfit.html'>plot_sep</a></span>(<span class='no'>f_soil</span>, <span class='kw'>lpos</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='st'>"topright"</span>, <span class='st'>"topright"</span>, <span class='st'>"topright"</span>, <span class='st'>"bottomright"</span>))</div><img src='test_data_from_UBA_2014-16.png' alt='' width='540' height='400' /><div class='input'> <span class='fu'>summary</span>(<span class='no'>f_soil</span>)$<span class='no'>bpar</span></div><div class='output co'>#> Estimate se_notrans t value Pr(>t) Lower
#> parent_0 76.55425583 0.943443834 81.1434164 4.422340e-30 74.602593306
#> k_parent 0.12081956 0.004815515 25.0896457 1.639665e-18 0.111257526
#> k_M1 0.84258650 0.930121206 0.9058889 1.871937e-01 0.085876305
#> k_M2 0.04210878 0.013729902 3.0669396 2.729137e-03 0.021450631
#> k_M3 0.01122919 0.008044866 1.3958205 8.804914e-02 0.002550985
#> f_parent_to_M1 0.32240199 0.278620411 1.1571370 1.295466e-01 NA
#> f_parent_to_M2 0.16099854 0.030548889 5.2701930 1.196191e-05 NA
#> f_M1_to_M3 0.27921500 0.314732717 0.8871496 1.920907e-01 0.015016888
#> f_M2_to_M3 0.55641332 0.650247079 0.8556952 2.004966e-01 0.005360551
#> Upper
#> parent_0 78.50591836
#> k_parent 0.13120340
#> k_M1 8.26714671
#> k_M2 0.08266187
#> k_M3 0.04942980
#> f_parent_to_M1 NA
#> f_parent_to_M2 NA
#> f_M1_to_M3 0.90777217
#> f_M2_to_M3 0.99658634</div><div class='input'> <span class='fu'><a href='mkinerrmin.html'>mkinerrmin</a></span>(<span class='no'>f_soil</span>)</div><div class='output co'>#> err.min n.optim df
#> All data 0.09649963 9 20
#> parent 0.04721283 2 6
#> M1 0.26551209 2 5
#> M2 0.20327575 2 5
#> M3 0.05196549 3 4</div></pre>
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