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    <h1>Datasets on aerobic soil metabolism of 2,4,5-T in six soils</h1>
    </div>

    
    <p>Time course of 2,4,5-trichlorophenoxyacetic acid, and the corresponding
 2,4,5-trichlorophenol and 2,4,5-trichloroanisole as recovered in diethylether
 extracts.</p>
    

    <pre><span class='no'>mccall81_245T</span></pre>
        
    <h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>

    <p>A dataframe containing the following variables.
  <dl class='dl-horizontal'>
    <dt><code>name</code></dt><dd>the name of the compound observed. Note that T245 is used as 
                       an acronym for 2,4,5-T. T245 is a legitimate object name
                       in R, which is necessary for specifying models using
                       <code><a href='mkinmod.html'>mkinmod</a></code>.</dd> 
    <dt><code>time</code></dt><dd>a numeric vector containing sampling times in days after
                       treatment</dd>
    <dt><code>value</code></dt><dd>a numeric vector containing concentrations in percent of applied radioactivity</dd>
    <dt><code>soil</code></dt><dd>a factor containing the name of the soil</dd>
  </dl></p>
    
    <h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>

    <p>McCall P, Vrona SA, Kelley SS (1981) Fate of uniformly carbon-14 ring labeled 2,4,5-Trichlorophenoxyacetic acid and 2,4-dichlorophenoxyacetic acid. J Agric Chem 29, 100-107
  <a href = 'http://dx.doi.org/10.1021/jf00103a026'>http://dx.doi.org/10.1021/jf00103a026</a></p>
    

    <h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
    <pre class="examples"><div class='input'>  <span class='no'>SFO_SFO_SFO</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinmod.html'>mkinmod</a></span>(<span class='kw'>T245</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'>"phenol"</span>),
                         <span class='kw'>phenol</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'>"anisole"</span>),
                         <span class='kw'>anisole</span> <span class='kw'>=</span> <span class='fu'>list</span>(<span class='kw'>type</span> <span class='kw'>=</span> <span class='st'>"SFO"</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='no'>fit.1</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO_SFO</span>, <span class='fu'>subset</span>(<span class='no'>mccall81_245T</span>, <span class='no'>soil</span> <span class='kw'>==</span> <span class='st'>"Commerce"</span>))</div><div class='output co'>#&gt; Model cost at call  1 :  13655.2 
#&gt; Model cost at call  2 :  13655.2 
#&gt; Model cost at call  8 :  9191.59 
#&gt; Model cost at call  16 :  5663.584 
#&gt; Model cost at call  17 :  5663.582 
#&gt; Model cost at call  18 :  5663.566 
#&gt; Model cost at call  19 :  5663.55 
#&gt; Model cost at call  23 :  3035.567 
#&gt; Model cost at call  24 :  3035.566 
#&gt; Model cost at call  26 :  3035.561 
#&gt; Model cost at call  27 :  3035.559 
#&gt; Model cost at call  28 :  3035.558 
#&gt; Model cost at call  30 :  2252.97 
#&gt; Model cost at call  31 :  2252.965 
#&gt; Model cost at call  32 :  2252.965 
#&gt; Model cost at call  36 :  2252.958 
#&gt; Model cost at call  37 :  1220.201 
#&gt; Model cost at call  38 :  1220.2 
#&gt; Model cost at call  39 :  1220.199 
#&gt; Model cost at call  41 :  1220.183 
#&gt; Model cost at call  45 :  507.1358 
#&gt; Model cost at call  48 :  507.1353 
#&gt; Model cost at call  52 :  198.5695 
#&gt; Model cost at call  55 :  198.5694 
#&gt; Model cost at call  60 :  175.8239 
#&gt; Model cost at call  63 :  175.8239 
#&gt; Model cost at call  67 :  170.6316 
#&gt; Model cost at call  69 :  170.6316 
#&gt; Model cost at call  74 :  165.881 
#&gt; Model cost at call  77 :  165.881 
#&gt; Model cost at call  81 :  161.6423 
#&gt; Model cost at call  84 :  161.6423 
#&gt; Model cost at call  88 :  158.2953 
#&gt; Model cost at call  91 :  158.2953 
#&gt; Model cost at call  95 :  156.7311 
#&gt; Model cost at call  97 :  156.731 
#&gt; Model cost at call  103 :  155.998 
#&gt; Model cost at call  106 :  155.998 
#&gt; Model cost at call  110 :  155.6263 
#&gt; Model cost at call  113 :  155.6262 
#&gt; Model cost at call  116 :  155.6262 
#&gt; Model cost at call  117 :  155.1202 
#&gt; Model cost at call  120 :  155.1202 
#&gt; Model cost at call  124 :  154.4133 
#&gt; Model cost at call  125 :  153.8489 
#&gt; Model cost at call  126 :  152.7413 
#&gt; Model cost at call  129 :  152.7413 
#&gt; Model cost at call  132 :  152.7413 
#&gt; Model cost at call  133 :  150.3995 
#&gt; Model cost at call  134 :  148.7256 
#&gt; Model cost at call  135 :  147.2618 
#&gt; Model cost at call  137 :  147.2618 
#&gt; Model cost at call  139 :  147.2618 
#&gt; Model cost at call  142 :  145.115 
#&gt; Model cost at call  144 :  145.115 
#&gt; Model cost at call  145 :  145.115 
#&gt; Model cost at call  146 :  145.115 
#&gt; Model cost at call  147 :  145.115 
#&gt; Model cost at call  150 :  143.7878 
#&gt; Model cost at call  157 :  142.8531 
#&gt; Model cost at call  160 :  142.8531 
#&gt; Model cost at call  164 :  142.7325 
#&gt; Model cost at call  167 :  142.7325 
#&gt; Model cost at call  169 :  142.7325 
#&gt; Model cost at call  172 :  141.8393 
#&gt; Model cost at call  173 :  141.8393 
#&gt; Model cost at call  174 :  141.8393 
#&gt; Model cost at call  179 :  141.3446 
#&gt; Model cost at call  180 :  141.3446 
#&gt; Model cost at call  181 :  141.3446 
#&gt; Model cost at call  186 :  141.1111 
#&gt; Model cost at call  193 :  140.7786 
#&gt; Model cost at call  200 :  140.451 
#&gt; Model cost at call  207 :  140.1395 
#&gt; Model cost at call  214 :  139.7903 
#&gt; Model cost at call  221 :  139.5476 
#&gt; Model cost at call  228 :  139.4441 
#&gt; Model cost at call  235 :  139.3204 
#&gt; Model cost at call  242 :  139.2508 
#&gt; Model cost at call  249 :  139.1891 
#&gt; Model cost at call  256 :  139.1561 
#&gt; Model cost at call  263 :  139.137 
#&gt; Model cost at call  270 :  139.1278 
#&gt; Model cost at call  271 :  139.1278 
#&gt; Model cost at call  279 :  139.1211 
#&gt; Model cost at call  280 :  139.1211 
#&gt; Model cost at call  281 :  139.1211 
#&gt; Model cost at call  282 :  139.1211 
#&gt; Model cost at call  286 :  139.1179 
#&gt; Model cost at call  287 :  139.1179 
#&gt; Model cost at call  291 :  139.1179 
#&gt; Model cost at call  294 :  139.1179 
#&gt; Model cost at call  298 :  139.1158 
#&gt; Model cost at call  299 :  139.1158 
#&gt; Model cost at call  302 :  139.1158 
#&gt; Model cost at call  310 :  139.1148 
#&gt; Model cost at call  311 :  139.1148 
#&gt; Model cost at call  315 :  139.1148 
#&gt; Model cost at call  322 :  139.1143 
#&gt; Model cost at call  323 :  139.1143 
#&gt; Model cost at call  326 :  139.1143 
#&gt; Model cost at call  334 :  139.114 
#&gt; Model cost at call  335 :  139.114 
#&gt; Model cost at call  338 :  139.114 
#&gt; Model cost at call  339 :  139.114 
#&gt; Model cost at call  346 :  139.1139 
#&gt; Model cost at call  347 :  139.1139 
#&gt; Model cost at call  350 :  139.1139 
#&gt; Model cost at call  351 :  139.1139 
#&gt; Model cost at call  358 :  139.1139 
#&gt; Model cost at call  359 :  139.1139 
#&gt; Model cost at call  362 :  139.1139 
#&gt; Model cost at call  363 :  139.1139 
#&gt; Model cost at call  370 :  139.1138 
#&gt; Model cost at call  382 :  139.1138 
#&gt; Model cost at call  390 :  139.1138 
#&gt; Model cost at call  395 :  139.1138 
#&gt; Model cost at call  403 :  139.1138 
#&gt; Model cost at call  408 :  139.1138 
#&gt; Model cost at call  416 :  139.1138 
#&gt; Model cost at call  421 :  139.1138 
#&gt; Model cost at call  429 :  139.1138 
#&gt; Model cost at call  434 :  139.1138 
#&gt; Model cost at call  442 :  139.1138 
#&gt; Model cost at call  447 :  139.1138 
#&gt; Model cost at call  455 :  139.1138 
#&gt; Model cost at call  460 :  139.1138 
#&gt; Model cost at call  468 :  139.1138 
#&gt; Model cost at call  473 :  139.1138 
#&gt; Model cost at call  481 :  139.1138 
#&gt; Model cost at call  486 :  139.1138 
#&gt; Model cost at call  494 :  139.1138 
#&gt; Model cost at call  499 :  139.1138 
#&gt; Model cost at call  507 :  139.1138 
#&gt; Model cost at call  512 :  139.1138 
#&gt; Model cost at call  519 :  139.1138 
#&gt; Model cost at call  520 :  139.1138 
#&gt; Model cost at call  525 :  139.1138 
#&gt; Model cost at call  538 :  139.1138 
#&gt; Model cost at call  545 :  139.1138 
#&gt; Model cost at call  546 :  139.1138 
#&gt; Model cost at call  551 :  139.1138 
#&gt; Model cost at call  558 :  139.1138 
#&gt; Model cost at call  559 :  139.1138 
#&gt; Model cost at call  564 :  139.1138 
#&gt; Model cost at call  571 :  139.1138 
#&gt; Model cost at call  580 :  139.1138 
#&gt; Model cost at call  588 :  139.1138 </div><div class='output co'>#&gt; <span class='warning'>Warning: Optimisation by method Port did not converge.</span>
#&gt; <span class='warning'>Convergence code is 1</span></div><div class='input'>    <span class='fu'>summary</span>(<span class='no'>fit.1</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; mkin version:    0.9.44.9000 
#&gt; R version:       3.3.2 
#&gt; Date of fit:     Fri Nov 18 15:19:33 2016 
#&gt; Date of summary: Fri Nov 18 15:19:33 2016 
#&gt; 
#&gt; 
#&gt; Warning: Optimisation by method Port did not converge.
#&gt; Convergence code is 1 
#&gt; 
#&gt; 
#&gt; Equations:
#&gt; d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
#&gt; d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol -
#&gt;            k_phenol_anisole * phenol
#&gt; d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole
#&gt; 
#&gt; Model predictions using solution type deSolve 
#&gt; 
#&gt; Fitted with method Port using 590 model solutions performed in 3.45 s
#&gt; 
#&gt; Weighting: none
#&gt; 
#&gt; Starting values for parameters to be optimised:
#&gt;                     value   type
#&gt; T245_0           100.9000  state
#&gt; k_T245_sink        0.1000 deparm
#&gt; k_T245_phenol      0.1001 deparm
#&gt; k_phenol_sink      0.1002 deparm
#&gt; k_phenol_anisole   0.1003 deparm
#&gt; k_anisole_sink     0.1004 deparm
#&gt; 
#&gt; Starting values for the transformed parameters actually optimised:
#&gt;                           value lower upper
#&gt; T245_0               100.900000  -Inf   Inf
#&gt; log_k_T245_sink       -2.302585  -Inf   Inf
#&gt; log_k_T245_phenol     -2.301586  -Inf   Inf
#&gt; log_k_phenol_sink     -2.300587  -Inf   Inf
#&gt; log_k_phenol_anisole  -2.299590  -Inf   Inf
#&gt; log_k_anisole_sink    -2.298593  -Inf   Inf
#&gt; 
#&gt; Fixed parameter values:
#&gt;           value  type
#&gt; phenol_0      0 state
#&gt; anisole_0     0 state
#&gt; 
#&gt; Optimised, transformed parameters with symmetric confidence intervals:
#&gt;                      Estimate Std. Error Lower Upper
#&gt; T245_0               103.9000         NA    NA    NA
#&gt; log_k_T245_sink       -4.1130         NA    NA    NA
#&gt; log_k_T245_phenol     -3.6120         NA    NA    NA
#&gt; log_k_phenol_sink    -26.3900         NA    NA    NA
#&gt; log_k_phenol_anisole  -0.9037         NA    NA    NA
#&gt; log_k_anisole_sink    -5.0090         NA    NA    NA
#&gt; 
#&gt; Parameter correlation:</div><div class='output co'>#&gt; <span class='warning'>Warning: Could not estimate covariance matrix; singular system:</span></div><div class='output co'>#&gt; Could not estimate covariance matrix; singular system:
#&gt; 
#&gt; Residual standard error: 2.78 on 18 degrees of freedom
#&gt; 
#&gt; Backtransformed parameters:
#&gt; Confidence intervals for internally transformed parameters are asymmetric.
#&gt; t-test (unrealistically) based on the assumption of normal distribution
#&gt; for estimators of untransformed parameters.
#&gt;                   Estimate   t value    Pr(&gt;t) Lower Upper
#&gt; T245_0           1.039e+02 4.282e+01 7.236e-20    NA    NA
#&gt; k_T245_sink      1.636e-02 8.901e-01 1.926e-01    NA    NA
#&gt; k_T245_phenol    2.701e-02 1.504e+00 7.498e-02    NA    NA
#&gt; k_phenol_sink    3.457e-12 1.230e-11 5.000e-01    NA    NA
#&gt; k_phenol_anisole 4.051e-01 2.518e+00 1.075e-02    NA    NA
#&gt; k_anisole_sink   6.679e-03 8.146e+00 9.469e-08    NA    NA
#&gt; 
#&gt; Chi2 error levels in percent:
#&gt;          err.min n.optim df
#&gt; All data  10.070       6 16
#&gt; T245       7.908       3  5
#&gt; phenol   106.445       2  5
#&gt; anisole    5.379       1  6
#&gt; 
#&gt; Resulting formation fractions:
#&gt;                       ff
#&gt; T245_sink      3.772e-01
#&gt; T245_phenol    6.228e-01
#&gt; phenol_sink    8.534e-12
#&gt; phenol_anisole 1.000e+00
#&gt; anisole_sink   1.000e+00
#&gt; 
#&gt; Estimated disappearance times:
#&gt;            DT50    DT90
#&gt; T245     15.982  53.091
#&gt; phenol    1.711   5.685
#&gt; anisole 103.784 344.763</div><div class='input'>
  <span class='co'># No covariance matrix and k_phenol_sink is really small, therefore fix it to zero</span>
  <span class='no'>fit.2</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='mkinfit.html'>mkinfit</a></span>(<span class='no'>SFO_SFO_SFO</span>, <span class='fu'>subset</span>(<span class='no'>mccall81_245T</span>, <span class='no'>soil</span> <span class='kw'>==</span> <span class='st'>"Commerce"</span>),
                 <span class='kw'>parms.ini</span> <span class='kw'>=</span> <span class='fu'>c</span>(<span class='kw'>k_phenol_sink</span> <span class='kw'>=</span> <span class='fl'>0</span>),
                 <span class='kw'>fixed_parms</span> <span class='kw'>=</span> <span class='st'>"k_phenol_sink"</span>, <span class='kw'>quiet</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
  <span class='fu'>summary</span>(<span class='no'>fit.2</span>, <span class='kw'>data</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; mkin version:    0.9.44.9000 
#&gt; R version:       3.3.2 
#&gt; Date of fit:     Fri Nov 18 15:19:35 2016 
#&gt; Date of summary: Fri Nov 18 15:19:35 2016 
#&gt; 
#&gt; Equations:
#&gt; d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
#&gt; d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol -
#&gt;            k_phenol_anisole * phenol
#&gt; d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole
#&gt; 
#&gt; Model predictions using solution type deSolve 
#&gt; 
#&gt; Fitted with method Port using 246 model solutions performed in 1.477 s
#&gt; 
#&gt; Weighting: none
#&gt; 
#&gt; Starting values for parameters to be optimised:
#&gt;                     value   type
#&gt; T245_0           100.9000  state
#&gt; k_T245_sink        0.1000 deparm
#&gt; k_T245_phenol      0.1001 deparm
#&gt; k_phenol_anisole   0.1002 deparm
#&gt; k_anisole_sink     0.1003 deparm
#&gt; 
#&gt; Starting values for the transformed parameters actually optimised:
#&gt;                           value lower upper
#&gt; T245_0               100.900000  -Inf   Inf
#&gt; log_k_T245_sink       -2.302585  -Inf   Inf
#&gt; log_k_T245_phenol     -2.301586  -Inf   Inf
#&gt; log_k_phenol_anisole  -2.300587  -Inf   Inf
#&gt; log_k_anisole_sink    -2.299590  -Inf   Inf
#&gt; 
#&gt; Fixed parameter values:
#&gt;               value   type
#&gt; phenol_0          0  state
#&gt; anisole_0         0  state
#&gt; k_phenol_sink     0 deparm
#&gt; 
#&gt; Optimised, transformed parameters with symmetric confidence intervals:
#&gt;                      Estimate Std. Error  Lower    Upper
#&gt; T245_0               103.9000    2.35200 98.930 108.8000
#&gt; log_k_T245_sink       -4.1130    0.13250 -4.390  -3.8350
#&gt; log_k_T245_phenol     -3.6120    0.05002 -3.716  -3.5070
#&gt; log_k_phenol_anisole  -0.9037    0.30580 -1.544  -0.2637
#&gt; log_k_anisole_sink    -5.0090    0.11180 -5.243  -4.7750
#&gt; 
#&gt; Parameter correlation:
#&gt;                        T245_0 log_k_T245_sink log_k_T245_phenol
#&gt; T245_0                1.00000         0.63761           -0.1742
#&gt; log_k_T245_sink       0.63761         1.00000           -0.3831
#&gt; log_k_T245_phenol    -0.17416        -0.38313            1.0000
#&gt; log_k_phenol_anisole -0.05948         0.08745           -0.3047
#&gt; log_k_anisole_sink   -0.16208        -0.60469            0.5227
#&gt;                      log_k_phenol_anisole log_k_anisole_sink
#&gt; T245_0                           -0.05948            -0.1621
#&gt; log_k_T245_sink                   0.08745            -0.6047
#&gt; log_k_T245_phenol                -0.30470             0.5227
#&gt; log_k_phenol_anisole              1.00000            -0.1774
#&gt; log_k_anisole_sink               -0.17744             1.0000
#&gt; 
#&gt; Residual standard error: 2.706 on 19 degrees of freedom
#&gt; 
#&gt; Backtransformed parameters:
#&gt; Confidence intervals for internally transformed parameters are asymmetric.
#&gt; t-test (unrealistically) based on the assumption of normal distribution
#&gt; for estimators of untransformed parameters.
#&gt;                   Estimate t value    Pr(&gt;t)     Lower     Upper
#&gt; T245_0           1.039e+02  44.160 6.462e-21 98.930000 108.80000
#&gt; k_T245_sink      1.636e-02   7.545 1.978e-07  0.012400   0.02159
#&gt; k_T245_phenol    2.701e-02  19.990 1.607e-14  0.024320   0.02999
#&gt; k_phenol_anisole 4.051e-01   3.270 2.014e-03  0.213600   0.76820
#&gt; k_anisole_sink   6.679e-03   8.942 1.544e-08  0.005285   0.00844
#&gt; 
#&gt; Chi2 error levels in percent:
#&gt;          err.min n.optim df
#&gt; All data   9.831       5 17
#&gt; T245       7.908       3  5
#&gt; phenol    99.808       1  6
#&gt; anisole    5.379       1  6
#&gt; 
#&gt; Resulting formation fractions:
#&gt;                    ff
#&gt; T245_sink      0.3772
#&gt; T245_phenol    0.6228
#&gt; phenol_anisole 1.0000
#&gt; phenol_sink    0.0000
#&gt; anisole_sink   1.0000
#&gt; 
#&gt; Estimated disappearance times:
#&gt;            DT50    DT90
#&gt; T245     15.982  53.091
#&gt; phenol    1.711   5.685
#&gt; anisole 103.784 344.763</div></pre>
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