From 38f9e15f0c972c1516ae737a2bca8d7789581bbd Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 6 Oct 2016 09:19:21 +0200 Subject: Static documentation rebuilt by pkgdown::build_site() --- docs/reference/DFOP.solution.html | 132 +++ docs/reference/Extract.mmkin.html | 1192 ++++++++++++++++++++++++ docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html | 129 +++ docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html | 128 +++ docs/reference/FOCUS_2006_HS_ref_A_to_F.html | 129 +++ docs/reference/FOCUS_2006_SFO_ref_A_to_F.html | 127 +++ docs/reference/FOCUS_2006_datasets.html | 130 +++ docs/reference/FOMC.solution.html | 147 +++ docs/reference/HS.solution.html | 131 +++ docs/reference/IORE.solution.html | 149 +++ docs/reference/SFO.solution.html | 124 +++ docs/reference/SFORB.solution.html | 133 +++ docs/reference/add_err.html | 196 ++++ docs/reference/endpoints.html | 123 +++ docs/reference/geometric_mean.html | 115 +++ docs/reference/ilr.html | 152 +++ docs/reference/index.html | 111 +++ docs/reference/mccall81_245T.html | 229 +++++ docs/reference/mkin_long_to_wide.html | 152 +++ docs/reference/mkin_wide_to_long.html | 131 +++ docs/reference/mkinds.html | 120 +++ docs/reference/mkinerrmin.html | 150 +++ docs/reference/mkinfit.html | 531 +++++++++++ docs/reference/mkinmod.html | 206 ++++ docs/reference/mkinparplot.html | 122 +++ docs/reference/mkinplot.html | 118 +++ docs/reference/mkinpredict.html | 318 +++++++ docs/reference/mkinresplot.html | 166 ++++ docs/reference/mkinsub.html | 147 +++ docs/reference/mmkin.html | 178 ++++ docs/reference/plot.mkinfit.html | 231 +++++ docs/reference/plot.mmkin.html | 156 ++++ docs/reference/print.mkinds.html | 109 +++ docs/reference/print.mkinmod.html | 109 +++ docs/reference/schaefer07_complex_case.html | 131 +++ docs/reference/summary.mkinfit.html | 229 +++++ docs/reference/synthetic_data_for_UBA.html | 157 ++++ docs/reference/transform_odeparms.html | 276 ++++++ docs/reference/unknown-10.png | Bin 0 -> 18197 bytes docs/reference/unknown-2.png | Bin 0 -> 10552 bytes docs/reference/unknown-4.png | Bin 0 -> 10559 bytes docs/reference/unknown-6.png | Bin 0 -> 7945 bytes docs/reference/unknown-8.png | Bin 0 -> 13728 bytes 43 files changed, 7314 insertions(+) create mode 100644 docs/reference/DFOP.solution.html create mode 100644 docs/reference/Extract.mmkin.html create mode 100644 docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html create mode 100644 docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html create mode 100644 docs/reference/FOCUS_2006_HS_ref_A_to_F.html create mode 100644 docs/reference/FOCUS_2006_SFO_ref_A_to_F.html create mode 100644 docs/reference/FOCUS_2006_datasets.html create mode 100644 docs/reference/FOMC.solution.html create mode 100644 docs/reference/HS.solution.html create mode 100644 docs/reference/IORE.solution.html create mode 100644 docs/reference/SFO.solution.html create mode 100644 docs/reference/SFORB.solution.html create mode 100644 docs/reference/add_err.html create mode 100644 docs/reference/endpoints.html create mode 100644 docs/reference/geometric_mean.html create mode 100644 docs/reference/ilr.html create mode 100644 docs/reference/index.html create mode 100644 docs/reference/mccall81_245T.html create mode 100644 docs/reference/mkin_long_to_wide.html create mode 100644 docs/reference/mkin_wide_to_long.html create mode 100644 docs/reference/mkinds.html create mode 100644 docs/reference/mkinerrmin.html create mode 100644 docs/reference/mkinfit.html create mode 100644 docs/reference/mkinmod.html create mode 100644 docs/reference/mkinparplot.html create mode 100644 docs/reference/mkinplot.html create mode 100644 docs/reference/mkinpredict.html create mode 100644 docs/reference/mkinresplot.html create mode 100644 docs/reference/mkinsub.html create mode 100644 docs/reference/mmkin.html create mode 100644 docs/reference/plot.mkinfit.html create mode 100644 docs/reference/plot.mmkin.html create mode 100644 docs/reference/print.mkinds.html create mode 100644 docs/reference/print.mkinmod.html create mode 100644 docs/reference/schaefer07_complex_case.html create mode 100644 docs/reference/summary.mkinfit.html create mode 100644 docs/reference/synthetic_data_for_UBA.html create mode 100644 docs/reference/transform_odeparms.html create mode 100644 docs/reference/unknown-10.png create mode 100644 docs/reference/unknown-2.png create mode 100644 docs/reference/unknown-4.png create mode 100644 docs/reference/unknown-6.png create mode 100644 docs/reference/unknown-8.png (limited to 'docs/reference') diff --git a/docs/reference/DFOP.solution.html b/docs/reference/DFOP.solution.html new file mode 100644 index 00000000..3422c206 --- /dev/null +++ b/docs/reference/DFOP.solution.html @@ -0,0 +1,132 @@ + + + + + + + + +DFOP.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Function describing decline from a defined starting value using the sum + of two exponential decline functions.

+ + + 
DFOP.solution(t, parent.0, k1, k2, g)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
k1
+
First kinetic constant.
+
k2
+
Second kinetic constant.
+
g
+
Fraction of the starting value declining according to the + first kinetic constant. +
+
+ +
+

Value

+ +

The value of the response variable at time t.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
  plot(function(x) DFOP.solution(x, 100, 5, 0.5, 0.3), 0, 4, ylim=c(0,100))
+
+
+
+
+ + +
+ + + 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 @@ + + + + + + + + +[.mmkin. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Subsetting method for mmkin objects

+
+ +
+
+ +

Subsetting method for mmkin objects.

+ + + 
# S3 method for mmkin
+[(x, i, j, ..., drop = FALSE)
+ +

Arguments

+
+
x
+
An mmkin object
+
i
+
Row index selecting the fits for specific models
+
j
+
Column index selecting the fits to specific datasets
+
...
+
Not used, only there to satisfy the generic method definition
+
drop
+
If FALSE, the method always returns an mmkin object, otherwise either + a list of mkinfit objects or a single mkinfit object.
+
+ +
+

Value

+ +

An object of class mmkin.

+
+ +

Examples

+ 
  # Only use one core, to pass R CMD check --as-cran
+  fits <- mmkin(c("SFO", "FOMC"), list(B = FOCUS_2006_B, C = FOCUS_2006_C),
+                cores = 1, quiet = TRUE)
+  fits["FOMC", ]
#>       dataset
+#> model  B       C      
+#>   FOMC List,42 List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[, "B"]
#>       dataset
+#> model  B      
+#>   SFO  List,42
+#>   FOMC List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[, "B", drop = TRUE]$FOMC
#> $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" 
+#> 
  fits["SFO", "B"]
#>      dataset
+#> model B      
+#>   SFO List,42
+#> attr(,"class")
+#> [1] "mmkin"
+#> 
  fits[["SFO", "B"]] # This is equivalent to
#> $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" 
+#> 
  fits["SFO", "B", drop = TRUE]
#> [[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" 
+#> 
+#>
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html new file mode 100644 index 00000000..5c0faa43 --- /dev/null +++ b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html @@ -0,0 +1,129 @@ + + + + + + + + +FOCUS_2006_DFOP_ref_A_to_B. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

A table with the fitted parameters and the resulting DT50 and DT90 values +generated with different software packages. Taken directly from FOCUS (2006). +The results from fitting the data with the Topfit software was removed, as +the initial concentration of the parent compound was fixed to a value of 100 +in this fit.

+ + + 
data(FOCUS_2006_DFOP_ref_A_to_B)
+ +
+

Format

+ +

A data frame containing the following variables. +

+
package
a factor giving the name of the software package
+
M0
The fitted initial concentration of the parent compound
+
f
The fitted f parameter
+
k1
The fitted k1 parameter
+
k2
The fitted k2 parameter
+
DT50
The resulting half-life of the parent compound
+
DT90
The resulting DT90 of the parent compound
+
dataset
The FOCUS dataset that was used
+

+
+ +
+

Source

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
data(FOCUS_2006_DFOP_ref_A_to_B)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html new file mode 100644 index 00000000..89faecbf --- /dev/null +++ b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html @@ -0,0 +1,128 @@ + + + + + + + + +FOCUS_2006_FOMC_ref_A_to_F. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

A table with the fitted parameters and the resulting DT50 and DT90 values +generated with different software packages. Taken directly from FOCUS (2006). +The results from fitting the data with the Topfit software was removed, as +the initial concentration of the parent compound was fixed to a value of 100 +in this fit.

+ + + 
data(FOCUS_2006_FOMC_ref_A_to_F)
+ +
+

Format

+ +

A data frame containing the following variables. +

+
package
a factor giving the name of the software package
+
M0
The fitted initial concentration of the parent compound
+
alpha
The fitted alpha parameter
+
beta
The fitted beta parameter
+
DT50
The resulting half-life of the parent compound
+
DT90
The resulting DT90 of the parent compound
+
dataset
The FOCUS dataset that was used
+

+
+ +
+

Source

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
data(FOCUS_2006_FOMC_ref_A_to_F)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/FOCUS_2006_HS_ref_A_to_F.html b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html new file mode 100644 index 00000000..2dfafec6 --- /dev/null +++ b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html @@ -0,0 +1,129 @@ + + + + + + + + +FOCUS_2006_HS_ref_A_to_F. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

A table with the fitted parameters and the resulting DT50 and DT90 values +generated with different software packages. Taken directly from FOCUS (2006). +The results from fitting the data with the Topfit software was removed, as +the initial concentration of the parent compound was fixed to a value of 100 +in this fit.

+ + + 
data(FOCUS_2006_HS_ref_A_to_F)
+ +
+

Format

+ +

A data frame containing the following variables. +

+
package
a factor giving the name of the software package
+
M0
The fitted initial concentration of the parent compound
+
tb
The fitted tb parameter
+
k1
The fitted k1 parameter
+
k2
The fitted k2 parameter
+
DT50
The resulting half-life of the parent compound
+
DT90
The resulting DT90 of the parent compound
+
dataset
The FOCUS dataset that was used
+

+
+ +
+

Source

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
data(FOCUS_2006_HS_ref_A_to_F)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html new file mode 100644 index 00000000..ed3a4aff --- /dev/null +++ b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html @@ -0,0 +1,127 @@ + + + + + + + + +FOCUS_2006_SFO_ref_A_to_F. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

A table with the fitted parameters and the resulting DT50 and DT90 values +generated with different software packages. Taken directly from FOCUS (2006). +The results from fitting the data with the Topfit software was removed, as +the initial concentration of the parent compound was fixed to a value of 100 +in this fit.

+ + + 
data(FOCUS_2006_SFO_ref_A_to_F)
+ +
+

Format

+ +

A data frame containing the following variables. +

+
package
a factor giving the name of the software package
+
M0
The fitted initial concentration of the parent compound
+
k
The fitted first-order degradation rate constant
+
DT50
The resulting half-life of the parent compound
+
DT90
The resulting DT90 of the parent compound
+
dataset
The FOCUS dataset that was used
+

+
+ +
+

Source

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
data(FOCUS_2006_SFO_ref_A_to_F)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/FOCUS_2006_datasets.html b/docs/reference/FOCUS_2006_datasets.html new file mode 100644 index 00000000..c1eacbd8 --- /dev/null +++ b/docs/reference/FOCUS_2006_datasets.html @@ -0,0 +1,130 @@ + + + + + + + + +FOCUS_2006_datasets. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Data taken from FOCUS (2006), p. 258.

+ + + 
FOCUS_2006_datasets
+ +
+

Format

+ +

6 datasets with observations on the following variables. +

+
name
a factor containing the name of the observed variable
+
time
a numeric vector containing time points
+
value
a numeric vector containing concentrations in percent of applied radioactivity
+

+
+ +
+

Source

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
FOCUS_2006_C
#>     name time value
+#> 1 parent    0  85.1
+#> 2 parent    1  57.9
+#> 3 parent    3  29.9
+#> 4 parent    7  14.6
+#> 5 parent   14   9.7
+#> 6 parent   28   6.6
+#> 7 parent   63   4.0
+#> 8 parent   91   3.9
+#> 9 parent  119   0.6
+#>
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/FOMC.solution.html b/docs/reference/FOMC.solution.html new file mode 100644 index 00000000..912cf414 --- /dev/null +++ b/docs/reference/FOMC.solution.html @@ -0,0 +1,147 @@ + + + + + + + + +FOMC.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

First-Order Multi-Compartment kinetics

+
+ +
+
+ +

Function describing exponential decline from a defined starting value, with + a decreasing rate constant.

+ +

The form given here differs slightly from the original reference by Gustafson + and Holden (1990). The parameter beta corresponds to 1/beta in the + original equation.

+ + + 
FOMC.solution(t, parent.0, alpha, beta)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
alpha
+
+ Shape parameter determined by coefficient of variation of rate constant + values.
+
beta
+
+ Location parameter. +
+
+ +
+

Note

+ +

The solution of the FOMC kinetic model reduces to the + SFO.solution for large values of alpha and + beta with + \(k = \frac{\beta}{\alpha}\).

+
+ +
+

Value

+ +

The value of the response variable at time t.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+

Gustafson DI and Holden LR (1990) Nonlinear pesticide dissipation in soil: A + new model based on spatial variability. Environmental Science and + Technology 24, 1032-1038

+
+ +

Examples

+ 
  plot(function(x) FOMC.solution(x, 100, 10, 2), 0, 2, ylim = c(0, 100))
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/HS.solution.html b/docs/reference/HS.solution.html new file mode 100644 index 00000000..994f8373 --- /dev/null +++ b/docs/reference/HS.solution.html @@ -0,0 +1,131 @@ + + + + + + + + +HS.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Hockey-Stick kinetics

+
+ +
+
+ +

Function describing two exponential decline functions with a break point + between them.

+ + + 
HS.solution(t, parent.0, k1, k2, tb)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
k1
+
First kinetic constant.
+
k2
+
Second kinetic constant.
+
tb
+
Break point. Before this time, exponential decline according + to k1 is calculated, after this time, exponential decline proceeds + according to k2.
+
+ +
+

Value

+ +

The value of the response variable at time t.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
  plot(function(x) HS.solution(x, 100, 2, 0.3, 0.5), 0, 2, ylim=c(0,100))
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/IORE.solution.html b/docs/reference/IORE.solution.html new file mode 100644 index 00000000..06f5c1ad --- /dev/null +++ b/docs/reference/IORE.solution.html @@ -0,0 +1,149 @@ + + + + + + + + +IORE.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Indeterminate order rate equation kinetics

+
+ +
+
+ +

Function describing exponential decline from a defined starting value, with + a concentration dependent rate constant.

+ + + 
IORE.solution(t, parent.0, k__iore, N)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
k__iore
+
Rate constant. Note that this depends on the concentration units used.
+
N
+
Exponent describing the nonlinearity of the rate equation
+
+ +
+

Note

+ +

The solution of the IORE kinetic model reduces to the + SFO.solution if N = 1. + The parameters of the IORE model can be transformed to equivalent parameters + of the FOMC mode - see the NAFTA guidance for details.

+
+ +
+

Value

+ +

The value of the response variable at time t.

+
+ +
+

References

+ +

NAFTA Technical Working Group on Pesticides (not dated) Guidance for + Evaluating and Calculating Degradation Kinetics in Environmental + Media

+
+ +

Examples

+ 
  plot(function(x) IORE.solution(x, 100, 0.2, 1.3), 0, 2,
+                                       ylim = c(0, 100))
  fit.fomc <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+  fit.iore <- mkinfit("IORE", FOCUS_2006_C, quiet = TRUE)
+  fit.iore.deS <- mkinfit("IORE", FOCUS_2006_C, solution_type = "deSolve", quiet = TRUE)
+
+  print(data.frame(coef(fit.fomc), coef(fit.iore), coef(fit.iore.deS),
+                   row.names = paste("model par", 1:3)))
#>             coef.fit.fomc. coef.fit.iore. coef.fit.iore.deS.
+#> model par 1    85.87489063      85.874891          85.874890
+#> model par 2     0.05192238      -4.826631          -4.826631
+#> model par 3     0.65096665       1.949403           1.949403
+#> 
  print(rbind(fomc = endpoints(fit.fomc)$distimes, iore = endpoints(fit.iore)$distimes,
+              iore.deS = endpoints(fit.iore)$distimes))
#>              DT50    DT90 DT50back
+#> fomc     1.785233 15.1479 4.559973
+#> iore     1.785233 15.1479 4.559973
+#> iore.deS 1.785233 15.1479 4.559973
+#>
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/SFO.solution.html b/docs/reference/SFO.solution.html new file mode 100644 index 00000000..9cf069d7 --- /dev/null +++ b/docs/reference/SFO.solution.html @@ -0,0 +1,124 @@ + + + + + + + + +SFO.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Single First-Order kinetics

+
+ +
+
+ +

Function describing exponential decline from a defined starting value.

+ + + 
SFO.solution(t, parent.0, k)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
k
+
Kinetic constant.
+
+ +
+

Value

+ +

The value of the response variable at time t.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
  ## Not run: plot(function(x) SFO.solution(x, 100, 3), 0, 2)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/SFORB.solution.html b/docs/reference/SFORB.solution.html new file mode 100644 index 00000000..57959f26 --- /dev/null +++ b/docs/reference/SFORB.solution.html @@ -0,0 +1,133 @@ + + + + + + + + +SFORB.solution. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Single First-Order Reversible Binding kinetics

+
+ +
+
+ +

Function describing the solution of the differential equations describing + the kinetic model with first-order terms for a two-way transfer from a free + to a bound fraction, and a first-order degradation term for the free + fraction. The initial condition is a defined amount in the free fraction and + no substance in the bound fraction.

+ + + 
SFORB.solution(t, parent.0, k_12, k_21, k_1output)
+ +

Arguments

+
+
t
+
Time.
+
parent.0
+
Starting value for the response variable at time zero.
+
k_12
+
Kinetic constant describing transfer from free to bound.
+
k_21
+
Kinetic constant describing transfer from bound to free.
+
k_1output
+
Kinetic constant describing degradation of the free fraction.
+
+ +
+

Value

+ +

The value of the response variable, which is the sum of free and bound + fractions at time t.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
  ## Not run: plot(function(x) SFORB.solution(x, 100, 0.5, 2, 3), 0, 2)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/add_err.html b/docs/reference/add_err.html new file mode 100644 index 00000000..cbc925ca --- /dev/null +++ b/docs/reference/add_err.html @@ -0,0 +1,196 @@ + + + + + + + + +add_err. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Normally distributed errors are added to data predicted for a specific + degradation model using mkinpredict. The variance of the error + may depend on the predicted value and is specified as a standard deviation.

+ + + 
add_err(prediction, sdfunc,
+          n = 1000, LOD = 0.1, reps = 2,
+          digits = 1, seed = NA)
+ +

Arguments

+
+
prediction
+
+ A prediction from a kinetic model as produced by mkinpredict. +
+
sdfunc
+
+ A function taking the predicted value as its only argument and returning + a standard deviation that should be used for generating the random error + terms for this value. +
+
n
+
+ The number of datasets to be generated. +
+
LOD
+
+ The limit of detection (LOD). Values that are below the LOD after adding + the random error will be set to NA. +
+
reps
+
+ The number of replicates to be generated within the datasets. +
+
digits
+
+ The number of digits to which the values will be rounded. +
+
seed
+
+ The seed used for the generation of random numbers. If NA, the seed + is not set. +
+
+ +
+

Value

+ +

A list of datasets compatible with mmkin, i.e. + the components of the list are datasets compatible with + mkinfit.

+
+ +
+

References

+ +

Ranke J and Lehmann R (2015) To t-test or not to t-test, that is the question. XV Symposium on Pesticide Chemistry 2-4 September 2015, Piacenza, Italy + http://chem.uft.uni-bremen.de/ranke/posters/piacenza_2015.pdf

+
+ +

Examples

+ 
# The kinetic model
+m_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
+                     M1 = mkinsub("SFO"), use_of_ff = "max")
Successfully compiled differential equation model from auto-generated C code.

+# Generate a prediction for a specific set of parameters
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
+
+# This is the prediction used for the "Type 2 datasets" on the Piacenza poster
+# from 2015
+d_SFO_SFO <- mkinpredict(m_SFO_SFO,
+                         c(k_parent = 0.1, f_parent_to_M1 = 0.5,
+                           k_M1 = log(2)/1000),
+                         c(parent = 100, M1 = 0),
+                         sampling_times)
+
+# Add an error term with a constant (independent of the value) standard deviation
+# of 10, and generate three datasets
+d_SFO_SFO_err <- add_err(d_SFO_SFO, function(x) 10, n = 3, seed = 123456789 )
+
+# Name the datasets for nicer plotting
+names(d_SFO_SFO_err) <- paste("Dataset", 1:3)
+
+# Name the model in the list of models (with only one member in this case)
+# for nicer plotting later on.
+# Be quiet and use the faster Levenberg-Marquardt algorithm, as the datasets
+# are easy and examples are run often. Use only one core not to offend CRAN
+# checks
+f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO),
+                   d_SFO_SFO_err, cores = 1,
+                   quiet = TRUE, method.modFit = "Marq")
+
+plot(f_SFO_SFO)

+# We would like to inspect the fit for dataset 3 more closely
+# Using double brackets makes the returned object an mkinfit object
+# instead of a list of mkinfit objects, so plot.mkinfit is used
+plot(f_SFO_SFO[[3]], show_residuals = TRUE)

+# If we use single brackets, we should give two indices (model and dataset),
+# and plot.mmkin is used
+plot(f_SFO_SFO[1, 3])

+
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/endpoints.html b/docs/reference/endpoints.html new file mode 100644 index 00000000..8ceb39d9 --- /dev/null +++ b/docs/reference/endpoints.html @@ -0,0 +1,123 @@ + + + + + + + + +endpoints. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function calculates DT50 and DT90 values as well as formation fractions from kinetic models +fitted with mkinfit. If the SFORB model was specified for one of the parents or metabolites, +the Eigenvalues are returned. These are equivalent to the rate constantes of the DFOP model, but +with the advantage that the SFORB model can also be used for metabolites.

+ + + 
endpoints(fit)
+ +

Arguments

+
+
fit
+
+ An object of class mkinfit. +
+
+ +
+

Note

+ +

The function is used internally by summary.mkinfit.

+
+ +
+

Value

+ +

A list with the components mentioned above.

+
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/geometric_mean.html b/docs/reference/geometric_mean.html new file mode 100644 index 00000000..1d9a9e66 --- /dev/null +++ b/docs/reference/geometric_mean.html @@ -0,0 +1,115 @@ + + + + + + + + +geometric_mean. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Calculate the geometric mean

+
+ +
+
+ +

Function calculating the geometric mean of numeric vectors

+ + + 
geometric_mean(x, na.rm = FALSE)
+ +

Arguments

+
+
x
+
A numeric vector
+
na.rm
+
Should NA values be ignored
+
+ +
+

Value

+ +

The geometric mean.

+
+ +

Examples

+ 
  geometric_mean(c(1,3, 9))
#> [1] 3
+#> 
  geometric_mean(c(1,3, NA))
#> [1] NA
+#> 
  geometric_mean(c(1,3, NA), na.rm = TRUE)
#> [1] 1.732051
+#>
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/ilr.html b/docs/reference/ilr.html new file mode 100644 index 00000000..355cbb78 --- /dev/null +++ b/docs/reference/ilr.html @@ -0,0 +1,152 @@ + + + + + + + + +ilr. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This implementation is a special case of the class of isometric log-ratio transformations.

+ + + 
ilr(x)
+  invilr(x)
+ +

Arguments

+
+
x
+
+ A numeric vector. Naturally, the forward transformation is only sensible for + vectors with all elements being greater than zero. +
+
+ +
+

Value

+ +

The result of the forward or backward transformation. The returned components always + sum to 1 for the case of the inverse log-ratio transformation.

+
+ +
+

References

+ +

Peter Filzmoser, Karel Hron (2008) Outlier Detection for Compositional Data Using Robust Methods. Math Geosci 40 233-248

+
+ +
+

See also

+ +

Another implementation can be found in R package robCompositions.

+
+ +

Examples

+ 
# Order matters
+ilr(c(0.1, 1, 10))
#> [1] -1.628174 -2.820079
+#> 
ilr(c(10, 1, 0.1))
#> [1] 1.628174 2.820079
+#> 
# Equal entries give ilr transformations with zeros as elements
+ilr(c(3, 3, 3))
#> [1] 0 0
+#> 
# Almost equal entries give small numbers
+ilr(c(0.3, 0.4, 0.3))
#> [1] -0.2034219  0.1174457
+#> 
# Only the ratio between the numbers counts, not their sum
+invilr(ilr(c(0.7, 0.29, 0.01)))
#> [1] 0.70 0.29 0.01
+#> 
invilr(ilr(2.1 * c(0.7, 0.29, 0.01)))
#> [1] 0.70 0.29 0.01
+#> 
# Inverse transformation of larger numbers gives unequal elements
+invilr(-10)
#> [1] 7.213536e-07 9.999993e-01
+#> 
invilr(c(-10, 0))
#> [1] 7.207415e-07 9.991507e-01 8.486044e-04
+#> 
# The sum of the elements of the inverse ilr is 1
+sum(invilr(c(-10, 0)))
#> [1] 1
+#> 
# This is why we do not need all elements of the inverse transformation to go back:
+a <- c(0.1, 0.3, 0.5)
+b <- invilr(a)
+length(b) # Four elements
#> [1] 4
+#> 
ilr(c(b[1:3], 1 - sum(b[1:3]))) # Gives c(0.1, 0.3, 0.5)
#> [1] 0.1 0.3 0.5
+#>
+
+
+

Author

+ + René Lehmann and Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/index.html b/docs/reference/index.html new file mode 100644 index 00000000..869f61dd --- /dev/null +++ b/docs/reference/index.html @@ -0,0 +1,111 @@ + + + + + + + + +Function reference. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

Function reference version 0.9.44.9000

+
+ +
+
+
+

Main functions

+

Essential functionality

+ +
+
mkinfit
+
+
+
mkinmod
+
+
+
mmkin
+
+
+
+
+
+

Show results

+

+ +
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/mccall81_245T.html b/docs/reference/mccall81_245T.html new file mode 100644 index 00000000..edfce55a --- /dev/null +++ b/docs/reference/mccall81_245T.html @@ -0,0 +1,229 @@ + + + + + + + + +mccall81_245T. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

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.

+ + + 
mccall81_245T
+ +
+

Format

+ +

A dataframe containing the following variables. +

+
name
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 + mkinmod.
+
time
a numeric vector containing sampling times in days after + treatment
+
value
a numeric vector containing concentrations in percent of applied radioactivity
+
soil
a factor containing the name of the soil
+

+
+ +
+

Source

+ +

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 + http://dx.doi.org/10.1021/jf00103a026

+
+ +

Examples

+ 
  SFO_SFO_SFO <- mkinmod(T245 = list(type = "SFO", to = "phenol"),
+                         phenol = list(type = "SFO", to = "anisole"),
+                         anisole = list(type = "SFO"))
Successfully compiled differential equation model from auto-generated C code.
  ## Not run: ------------------------------------
+#     fit.1 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"))
+#     summary(fit.1, data = FALSE)
+#   
+## ---------------------------------------------
+  # No covariance matrix and k_phenol_sink is really small, therefore fix it to zero
+  fit.2 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"),
+                 parms.ini = c(k_phenol_sink = 0),
+                 fixed_parms = "k_phenol_sink", quiet = TRUE)
+  summary(fit.2, data = FALSE)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.1 
+#> Date of fit:     Thu Oct  6 09:17:57 2016 
+#> Date of summary: Thu Oct  6 09:17:57 2016 
+#> 
+#> Equations:
+#> d_T245 = - k_T245_sink * T245 - k_T245_phenol * T245
+#> d_phenol = + k_T245_phenol * T245 - k_phenol_sink * phenol -
+#>            k_phenol_anisole * phenol
+#> d_anisole = + k_phenol_anisole * phenol - k_anisole_sink * anisole
+#> 
+#> Model predictions using solution type deSolve 
+#> 
+#> Fitted with method Port using 246 model solutions performed in 1.508 s
+#> 
+#> Weighting: none
+#> 
+#> Starting values for parameters to be optimised:
+#>                     value   type
+#> T245_0           100.9000  state
+#> k_T245_sink        0.1000 deparm
+#> k_T245_phenol      0.1001 deparm
+#> k_phenol_anisole   0.1002 deparm
+#> k_anisole_sink     0.1003 deparm
+#> 
+#> Starting values for the transformed parameters actually optimised:
+#>                           value lower upper
+#> T245_0               100.900000  -Inf   Inf
+#> log_k_T245_sink       -2.302585  -Inf   Inf
+#> log_k_T245_phenol     -2.301586  -Inf   Inf
+#> log_k_phenol_anisole  -2.300587  -Inf   Inf
+#> log_k_anisole_sink    -2.299590  -Inf   Inf
+#> 
+#> Fixed parameter values:
+#>               value   type
+#> phenol_0          0  state
+#> anisole_0         0  state
+#> k_phenol_sink     0 deparm
+#> 
+#> Optimised, transformed parameters with symmetric confidence intervals:
+#>                      Estimate Std. Error  Lower    Upper
+#> T245_0               103.9000    2.35200 98.930 108.8000
+#> log_k_T245_sink       -4.1130    0.13250 -4.390  -3.8350
+#> log_k_T245_phenol     -3.6120    0.05002 -3.716  -3.5070
+#> log_k_phenol_anisole  -0.9037    0.30580 -1.544  -0.2637
+#> log_k_anisole_sink    -5.0090    0.11180 -5.243  -4.7750
+#> 
+#> Parameter correlation:
+#>                        T245_0 log_k_T245_sink log_k_T245_phenol
+#> T245_0                1.00000         0.63761           -0.1742
+#> log_k_T245_sink       0.63761         1.00000           -0.3831
+#> log_k_T245_phenol    -0.17416        -0.38313            1.0000
+#> log_k_phenol_anisole -0.05948         0.08745           -0.3047
+#> log_k_anisole_sink   -0.16208        -0.60469            0.5227
+#>                      log_k_phenol_anisole log_k_anisole_sink
+#> T245_0                           -0.05948            -0.1621
+#> log_k_T245_sink                   0.08745            -0.6047
+#> log_k_T245_phenol                -0.30470             0.5227
+#> log_k_phenol_anisole              1.00000            -0.1774
+#> log_k_anisole_sink               -0.17744             1.0000
+#> 
+#> Residual standard error: 2.706 on 19 degrees of freedom
+#> 
+#> Backtransformed parameters:
+#> Confidence intervals for internally transformed parameters are asymmetric.
+#> t-test (unrealistically) based on the assumption of normal distribution
+#> for estimators of untransformed parameters.
+#>                   Estimate t value    Pr(>t)     Lower     Upper
+#> T245_0           1.039e+02  44.160 6.462e-21 98.930000 108.80000
+#> k_T245_sink      1.636e-02   7.545 1.978e-07  0.012400   0.02159
+#> k_T245_phenol    2.701e-02  19.990 1.607e-14  0.024320   0.02999
+#> k_phenol_anisole 4.051e-01   3.270 2.014e-03  0.213600   0.76820
+#> k_anisole_sink   6.679e-03   8.942 1.544e-08  0.005285   0.00844
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   9.831       5 17
+#> T245       7.908       3  5
+#> phenol    99.808       1  6
+#> anisole    5.379       1  6
+#> 
+#> Resulting formation fractions:
+#>                    ff
+#> T245_sink      0.3772
+#> T245_phenol    0.6228
+#> phenol_anisole 1.0000
+#> phenol_sink    0.0000
+#> anisole_sink   1.0000
+#> 
+#> Estimated disappearance times:
+#>            DT50    DT90
+#> T245     15.982  53.091
+#> phenol    1.711   5.685
+#> anisole 103.784 344.763
+#>
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/mkin_long_to_wide.html b/docs/reference/mkin_long_to_wide.html new file mode 100644 index 00000000..5b1a8353 --- /dev/null +++ b/docs/reference/mkin_long_to_wide.html @@ -0,0 +1,152 @@ + + + + + + + + +mkin_long_to_wide. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function takes a dataframe in the long form as required by modCost + and converts it into a dataframe with one independent variable and several + dependent variables as columns.

+ + + 
mkin_long_to_wide(long_data, time = "time", outtime = "time")
+ +

Arguments

+
+
long_data
+
+ The dataframe must contain one variable called "time" with the time values specified by the + time argument, one column called "name" with the grouping of the observed values, and + finally one column of observed values called "value". +
+
time
+
+ The name of the time variable in the long input data. +
+
outtime
+
+ The name of the time variable in the wide output data. +
+
+ +
+

Value

+ +

Dataframe in wide format.

+
+ +

Examples

+ 
mkin_long_to_wide(FOCUS_2006_D)
#>    time parent    m1
+#> 1     0  99.46  0.00
+#> 2     0 102.04  0.00
+#> 3     1  93.50  4.84
+#> 4     1  92.50  5.64
+#> 5     3  63.23 12.91
+#> 6     3  68.99 12.96
+#> 7     7  52.32 22.97
+#> 8     7  55.13 24.47
+#> 9    14  27.27 41.69
+#> 10   14  26.64 33.21
+#> 11   21  11.50 44.37
+#> 12   21  11.64 46.44
+#> 13   35   2.85 41.22
+#> 14   35   2.91 37.95
+#> 15   50   0.69 41.19
+#> 16   50   0.63 40.01
+#> 17   75   0.05 40.09
+#> 18   75   0.06 33.85
+#> 19  100     NA 31.04
+#> 20  100     NA 33.13
+#> 21  120     NA 25.15
+#> 22  120     NA 33.31
+#>
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkin_wide_to_long.html b/docs/reference/mkin_wide_to_long.html new file mode 100644 index 00000000..2a70ebbe --- /dev/null +++ b/docs/reference/mkin_wide_to_long.html @@ -0,0 +1,131 @@ + + + + + + + + +mkin_wide_to_long. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function simply takes a dataframe with one independent variable and several + dependent variable and converts it into the long form as required by modCost.

+ + + 
mkin_wide_to_long(wide_data, time = "t")
+ +

Arguments

+
+
wide_data
+
+ The dataframe must contain one variable with the time values specified by the + time argument and usually more than one column of observed values. +
+
time
+
+ The name of the time variable. +
+
+ +
+

Value

+ +

Dataframe in long format as needed for modCost.

+
+ +

Examples

+ 
wide <- data.frame(t = c(1,2,3), x = c(1,4,7), y = c(3,4,5))
+mkin_wide_to_long(wide)
#>   name time value
+#> 1    x    1     1
+#> 2    x    2     4
+#> 3    x    3     7
+#> 4    y    1     3
+#> 5    y    2     4
+#> 6    y    3     5
+#>
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinds.html b/docs/reference/mkinds.html new file mode 100644 index 00000000..0b4341aa --- /dev/null +++ b/docs/reference/mkinds.html @@ -0,0 +1,120 @@ + + + + + + + + +mkinds. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

A dataset class for mkin

+
+ +
+
+ +

A dataset class for mkin

+ + + 
mkinds
+ +
+

Format

+ +

An R6Class generator object.

+
+ +
+

Fields

+ +

+

+
title
A full title for the dataset

+

sampling
times The sampling times

+

time_unit
The time unit

+

observed
Names of the observed compounds

+

unit
The unit of the observations

+

replicates
The number of replicates

+

data
A dataframe with at least the columns name, time and value +in order to be compatible with mkinfit
+

+
+ +

Examples

+ 
mds <- mkinds$new("FOCUS A", FOCUS_2006_A)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/mkinerrmin.html b/docs/reference/mkinerrmin.html new file mode 100644 index 00000000..cd9faf1a --- /dev/null +++ b/docs/reference/mkinerrmin.html @@ -0,0 +1,150 @@ + + + + + + + + +mkinerrmin. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function uses optimize in order to iteratively find the +smallest relative error still resulting in passing the chi-squared test +as defined in the FOCUS kinetics report from 2006.

+ + + 
mkinerrmin(fit, alpha = 0.05)
+ +

Arguments

+
+
fit
+
+ an object of class mkinfit. +
+
alpha
+
+ The confidence level chosen for the chi-squared test. +
+
+ +
+

Value

+ +

A dataframe with the following components:

+

The dataframe has one row for the total dataset and one further row for + each observed state variable in the model.

+
+ +
+

Details

+ +

This function is used internally by summary.mkinfit.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
+                  m1 = list(type = "SFO"),
+                  use_of_ff = "max")
Successfully compiled differential equation model from auto-generated C code.

+fit_FOCUS_D = mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+round(mkinerrmin(fit_FOCUS_D), 4)
#>          err.min n.optim df
+#> All data  0.0640       4 15
+#> parent    0.0646       2  7
+#> m1        0.0469       2  8
+#> 
fit_FOCUS_E = mkinfit(SFO_SFO, FOCUS_2006_E, quiet = TRUE)
+round(mkinerrmin(fit_FOCUS_E), 4)
#>          err.min n.optim df
+#> All data  0.1544       4 13
+#> parent    0.1659       2  7
+#> m1        0.1095       2  6
+#>
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html new file mode 100644 index 00000000..d1441f8b --- /dev/null +++ b/docs/reference/mkinfit.html @@ -0,0 +1,531 @@ + + + + + + + + +mkinfit. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function uses the Flexible Modelling Environment package + FME to create a function calculating the model cost, i.e. the + deviation between the kinetic model and the observed data. This model cost is + then minimised using the Port algorithm nlminb, + using the specified initial or fixed parameters and starting values. + Per default, parameters in the kinetic models are internally transformed in order + to better satisfy the assumption of a normal distribution of their estimators. + In each step of the optimsation, the kinetic model is solved using the + function mkinpredict. The variance of the residuals for each + observed variable can optionally be iteratively reweighted until convergence + using the argument reweight.method = "obs".

+ + + 
mkinfit(mkinmod, observed,
+  parms.ini = "auto",
+  state.ini = "auto",
+  fixed_parms = NULL, fixed_initials = names(mkinmod$diffs)[-1],
+  from_max_mean = FALSE,
+  solution_type = c("auto", "analytical", "eigen", "deSolve"),
+  method.ode = "lsoda",
+  use_compiled = "auto",
+  method.modFit = c("Port", "Marq", "SANN", "Nelder-Mead", "BFGS", "CG", "L-BFGS-B"),
+  maxit.modFit = "auto",
+  control.modFit = list(),
+  transform_rates = TRUE,
+  transform_fractions = TRUE,
+  plot = FALSE, quiet = FALSE, err = NULL, weight = "none",
+  scaleVar = FALSE,
+  atol = 1e-8, rtol = 1e-10, n.outtimes = 100,
+  reweight.method = NULL,
+  reweight.tol = 1e-8, reweight.max.iter = 10,
+  trace_parms = FALSE, ...)
+ +

Arguments

+
+
mkinmod
+
+ A list of class mkinmod, containing the kinetic model to be + fitted to the data, or one of the shorthand names ("SFO", "FOMC", "DFOP", + "HS", "SFORB"). If a shorthand name is given, a parent only degradation + model is generated for the variable with the highest value in + observed. +
+
observed
+
+ The observed data. It has to be in the long format as described in + modFit, i.e. the first column called "name" must contain the + name of the observed variable for each data point. The second column must + contain the times of observation, named "time". The third column must be + named "value" and contain the observed values. Optionally, a further column + can contain weights for each data point. Its name must be passed as a + further argument named err which is then passed on to + modFit. +
+
parms.ini
+
+ A named vector of initial values for the parameters, including parameters + to be optimised and potentially also fixed parameters as indicated by + fixed_parms. If set to "auto", initial values for rate constants + are set to default values. Using parameter names that are not in the model + gives an error. + + It is possible to only specify a subset of the parameters that the model + needs. You can use the parameter lists "bparms.ode" from a previously + fitted model, which contains the differential equation parameters from this + model. This works nicely if the models are nested. An example is given + below. +
+
state.ini
+
+ A named vector of initial values for the state variables of the model. In + case the observed variables are represented by more than one model + variable, the names will differ from the names of the observed variables + (see map component of mkinmod). The default is to set + the initial value of the first model variable to the mean of the time zero + values for the variable with the maximum observed value, and all others to 0. + If this variable has no time zero observations, its initial value is set to 100. +
+
fixed_parms
+
+ The names of parameters that should not be optimised but rather kept at the + values specified in parms.ini. +
+
fixed_initials
+
+ The names of model variables for which the initial state at time 0 should + be excluded from the optimisation. Defaults to all state variables except + for the first one. +
+
from_max_mean
+
+ If this is set to TRUE, and the model has only one observed variable, then + data before the time of the maximum observed value (after averaging for each + sampling time) are discarded, and this time is subtracted from all + remaining time values, so the time of the maximum observed mean value is + the new time zero. +
+
solution_type
+
+ If set to "eigen", the solution of the system of differential equations is + based on the spectral decomposition of the coefficient matrix in cases that + this is possible. If set to "deSolve", a numerical ode solver from package + deSolve is used. If set to "analytical", an analytical + solution of the model is used. This is only implemented for simple + degradation experiments with only one state variable, i.e. with no + metabolites. The default is "auto", which uses "analytical" if possible, + otherwise "eigen" if the model can be expressed using eigenvalues and + eigenvectors, and finally "deSolve" for the remaining models (time + dependence of degradation rates and metabolites). This argument is passed + on to the helper function mkinpredict. +
+
method.ode
+
+ The solution method passed via mkinpredict to + ode in case the solution type is "deSolve". The default + "lsoda" is performant, but sometimes fails to converge. +
+
use_compiled
+
+ If set to FALSE, no compiled version of the mkinmod + model is used, in the calls to mkinpredict even if + a compiled verion is present. +
+
method.modFit
+
+ The optimisation method passed to modFit. + + In order to optimally deal with problems where local minima occur, the + "Port" algorithm is now used per default as it is less prone to get trapped + in local minima and depends less on starting values for parameters than + the Levenberg Marquardt variant selected by "Marq". However, "Port" needs + more iterations. + + The former default "Marq" is the Levenberg Marquardt algorithm + nls.lm from the package minpack.lm and usually needs + the least number of iterations. + + The "Pseudo" algorithm is not included because it needs finite parameter bounds + which are currently not supported. + + The "Newton" algorithm is not included because its number of iterations + can not be controlled by control.modFit and it does not appear + to provide advantages over the other algorithms. +
+
maxit.modFit
+
+ Maximum number of iterations in the optimisation. If not "auto", this will + be passed to the method called by modFit, overriding + what may be specified in the next argument control.modFit. +
+
control.modFit
+
+ Additional arguments passed to the optimisation method used by + modFit. +
+
transform_rates
+
+ Boolean specifying if kinetic rate constants should be transformed in the + model specification used in the fitting for better compliance with the + assumption of normal distribution of the estimator. If TRUE, also + alpha and beta parameters of the FOMC model are log-transformed, as well + as k1 and k2 rate constants for the DFOP and HS models and the break point + tb of the HS model. + If FALSE, zero is used as a lower bound for the rates in the optimisation. +
+
transform_fractions
+
+ Boolean specifying if formation fractions constants should be transformed in the + model specification used in the fitting for better compliance with the + assumption of normal distribution of the estimator. The default (TRUE) is + to do transformations. If TRUE, the g parameter of the DFOP and HS + models are also transformed, as they can also be seen as compositional + data. The transformation used for these transformations is the + ilr transformation. +
+
plot
+
+ Should the observed values and the numerical solutions be plotted at each + stage of the optimisation? +
+
quiet
+
+ Suppress printing out the current model cost after each improvement? +
+
err
+
either NULL, or the name of the column with the + error estimates, used to weigh the residuals (see details of + modCost); if NULL, then the residuals are not weighed. +
+
weight
+
+ only if err=NULL: how to weight the residuals, one of "none", + "std", "mean", see details of modCost. +
+
scaleVar
+
+ Will be passed to modCost. Default is not to scale Variables + according to the number of observations. +
+
atol
+
+ Absolute error tolerance, passed to ode. Default is 1e-8, + lower than in lsoda. +
+
rtol
+
+ Absolute error tolerance, passed to ode. Default is 1e-10, + much lower than in lsoda. +
+
n.outtimes
+
+ The length of the dataseries that is produced by the model prediction + function mkinpredict. This impacts the accuracy of + the numerical solver if that is used (see solution_type argument. + The default value is 100. +
+
reweight.method
+
+ The method used for iteratively reweighting residuals, also known + as iteratively reweighted least squares (IRLS). Default is NULL, + the other method implemented is called "obs", meaning that each + observed variable is assumed to have its own variance, this is + estimated from the fit and used for weighting the residuals + in each iteration until convergence of this estimate up to + reweight.tol or up to the maximum number of iterations + specified by reweight.max.iter. +
+
reweight.tol
+
+ Tolerance for convergence criterion for the variance components + in IRLS fits. +
+
reweight.max.iter
+
+ Maximum iterations in IRLS fits. +
+
trace_parms
+
+ Should a trace of the parameter values be listed? +
+
&#8230;
+
+ Further arguments that will be passed to modFit. +
+
+ +
+

Value

+ +

A list with "mkinfit" and "modFit" in the class attribute. + A summary can be obtained by summary.mkinfit.

+
+ +
+

See also

+ +

Plotting methods plot.mkinfit and + mkinparplot.

+

Fitting of several models to several datasets in a single call to + mmkin.

+
+ +
+

Note

+ +

The implementation of iteratively reweighted least squares is inspired by the + work of the KinGUII team at Bayer Crop Science (Walter Schmitt and Zhenglei + Gao). A similar implemention can also be found in CAKE 2.0, which is the + other GUI derivative of mkin, sponsored by Syngenta.

+
+ +
+

Note

+ +

When using the "IORE" submodel for metabolites, fitting with + "transform_rates = TRUE" (the default) often leads to failures of the + numerical ODE solver. In this situation it may help to switch off the + internal rate transformation.

+
+ +

Examples

+ 
# Use shorthand notation for parent only degradation
+fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
+summary(fit)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.1 
+#> Date of fit:     Thu Oct  6 09:17:59 2016 
+#> Date of summary: Thu Oct  6 09:17:59 2016 
+#> 
+#> Equations:
+#> d_parent = - (alpha/beta) * 1/((time/beta) + 1) * parent
+#> 
+#> Model predictions using solution type analytical 
+#> 
+#> Fitted with method Port using 64 model solutions performed in 0.153 s
+#> 
+#> Weighting: none
+#> 
+#> Starting values for parameters to be optimised:
+#>          value   type
+#> parent_0  85.1  state
+#> alpha      1.0 deparm
+#> beta      10.0 deparm
+#> 
+#> Starting values for the transformed parameters actually optimised:
+#>               value lower upper
+#> parent_0  85.100000  -Inf   Inf
+#> log_alpha  0.000000  -Inf   Inf
+#> log_beta   2.302585  -Inf   Inf
+#> 
+#> Fixed parameter values:
+#> None
+#> 
+#> Optimised, transformed parameters with symmetric confidence intervals:
+#>           Estimate Std. Error    Lower   Upper
+#> parent_0  85.87000     2.2460 80.38000 91.3700
+#> log_alpha  0.05192     0.1605 -0.34080  0.4446
+#> log_beta   0.65100     0.2801 -0.03452  1.3360
+#> 
+#> Parameter correlation:
+#>           parent_0 log_alpha log_beta
+#> parent_0    1.0000   -0.2033  -0.3624
+#> log_alpha  -0.2033    1.0000   0.9547
+#> log_beta   -0.3624    0.9547   1.0000
+#> 
+#> Residual standard error: 2.275 on 6 degrees of freedom
+#> 
+#> Backtransformed parameters:
+#> Confidence intervals for internally transformed parameters are asymmetric.
+#> t-test (unrealistically) based on the assumption of normal distribution
+#> for estimators of untransformed parameters.
+#>          Estimate t value    Pr(>t)   Lower  Upper
+#> parent_0   85.870  38.230 1.069e-08 80.3800 91.370
+#> alpha       1.053   6.231 3.953e-04  0.7112  1.560
+#> beta        1.917   3.570 5.895e-03  0.9661  3.806
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   6.657       3  6
+#> parent     6.657       3  6
+#> 
+#> Estimated disappearance times:
+#>         DT50  DT90 DT50back
+#> parent 1.785 15.15     4.56
+#> 
+#> Data:
+#>  time variable observed predicted residual
+#>     0   parent     85.1    85.875  -0.7749
+#>     1   parent     57.9    55.191   2.7091
+#>     3   parent     29.9    31.845  -1.9452
+#>     7   parent     14.6    17.012  -2.4124
+#>    14   parent      9.7     9.241   0.4590
+#>    28   parent      6.6     4.754   1.8460
+#>    63   parent      4.0     2.102   1.8977
+#>    91   parent      3.9     1.441   2.4590
+#>   119   parent      0.6     1.092  -0.4919
+#> 

+# One parent compound, one metabolite, both single first order.
+# Use mkinsub for convenience in model formulation. Pathway to sink included per default.
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
+                           solution_type = "eigen", quiet = TRUE)))
#>    user  system elapsed 
+#>   1.252   1.176   0.914 
+#> 
coef(fit)
#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
+#>          99.59848          -3.03822          -2.98030          -5.24750 
+#> 
endpoints(fit)
#> $ff
+#> parent_sink   parent_m1     m1_sink 
+#>    0.485524    0.514476    1.000000 
+#> 
+#> $SFORB
+#> logical(0)
+#> 
+#> $distimes
+#>              DT50      DT90
+#> parent   7.022929  23.32967
+#> m1     131.760712 437.69961
+#> 
+#> 
## Not run: ------------------------------------
+# # deSolve is slower when no C compiler (gcc) was available during model generation
+# print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D, 
+#                            solution_type = "deSolve")))
+# coef(fit.deSolve)
+# endpoints(fit.deSolve)
+## ---------------------------------------------
+
+# Use stepwise fitting, using optimised parameters from parent only fit, FOMC
+## Not run: ------------------------------------
+# FOMC_SFO <- mkinmod(
+#   parent = mkinsub("FOMC", "m1"),
+#   m1 = mkinsub("SFO"))
+# # Fit the model to the FOCUS example dataset D using defaults
+# fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D)
+# # Use starting parameters from parent only FOMC fit
+# fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, plot=TRUE)
+# fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D, 
+#   parms.ini = fit.FOMC$bparms.ode, plot=TRUE)
+# 
+# # Use stepwise fitting, using optimised parameters from parent only fit, SFORB
+# SFORB_SFO <- mkinmod(
+#   parent = list(type = "SFORB", to = "m1", sink = TRUE),
+#   m1 = list(type = "SFO"))
+# # Fit the model to the FOCUS example dataset D using defaults
+# fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D)
+# fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve")
+# # Use starting parameters from parent only SFORB fit (not really needed in this case)
+# fit.SFORB = mkinfit("SFORB", FOCUS_2006_D)
+# fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode)
+## ---------------------------------------------
+
+## Not run: ------------------------------------
+# # Weighted fits, including IRLS
+# SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"),
+#                       m1 = mkinsub("SFO"), use_of_ff = "max")
+# f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D)
+# summary(f.noweight)
+# f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs")
+# summary(f.irls)
+# f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean")
+# summary(f.w.mean)
+# f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value")
+# summary(f.w.value)
+## ---------------------------------------------
+
+## Not run: ------------------------------------
+# # Manual weighting
+# dw <- FOCUS_2006_D
+# errors <- c(parent = 2, m1 = 1)
+# dw$err.man <- errors[FOCUS_2006_D$name]
+# f.w.man <- mkinfit(SFO_SFO.ff, dw, err = "err.man")
+# summary(f.w.man)
+# f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man",
+#                        reweight.method = "obs")
+# summary(f.w.man.irls)
+## ---------------------------------------------
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html new file mode 100644 index 00000000..9dd8fca0 --- /dev/null +++ b/docs/reference/mkinmod.html @@ -0,0 +1,206 @@ + + + + + + + + +mkinmod. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

The function usually takes several expressions, each assigning a compound name to + a list, specifying the kinetic model type and reaction or transfer to other + observed compartments. Instead of specifying several expressions, a list + of lists can be given in the speclist argument.

+ +

For the definition of model types and their parameters, the equations given + in the FOCUS and NAFTA guidance documents are used.

+ + + 
mkinmod(..., use_of_ff = "min", speclist = NULL, quiet = FALSE, verbose = FALSE)
+ +

Arguments

+
+
...
+
+ For each observed variable, a list has to be specified as an argument, containing + at least a component type, specifying the type of kinetics to use + for the variable. Currently, single first order kinetics "SFO", + indeterminate order rate equation kinetics "IORE", or + single first order with reversible binding "SFORB" are implemented for all + variables, while + "FOMC", "DFOP" and "HS" can additionally be chosen for the first + variable which is assumed to be the source compartment. + Additionally, each component of the list can include a character vector to, + specifying names of variables to which a transfer is to be assumed in the + model. + If the argument use_of_ff is set to "min" (default) and the model for + the compartment is "SFO" or "SFORB", an additional component of the list + can be "sink=FALSE" effectively fixing the flux to sink to zero. +
+
use_of_ff
+
+ Specification of the use of formation fractions in the model equations and, if + applicable, the coefficient matrix. If "min", a minimum use of formation + fractions is made in order to avoid fitting the product of formation fractions + and rate constants. If "max", formation fractions are always used. +
+
speclist
+
+ The specification of the observed variables and their submodel types and + pathways can be given as a single list using this argument. Default is NULL. +
+
quiet
+
+ Should messages be suppressed? +
+
verbose
+
+ If TRUE, passed to cfunction if applicable to give + detailed information about the C function being built. +
+
+ +
+

Value

+ +

A list of class mkinmod for use with mkinfit, containing

+
+ +
+

Note

+ +

The IORE submodel is not well tested (yet). When using this model for metabolites, + you may want to read the second note in the help page to + mkinfit.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+

NAFTA Technical Working Group on Pesticides (not dated) Guidance for + Evaluating and Calculating Degradation Kinetics in Environmental + Media

+
+ +

Examples

+ 
# Specify the SFO model (this is not needed any more, as we can now mkinfit("SFO", ...)
+SFO <- mkinmod(parent = list(type = "SFO"))
+
+# One parent compound, one metabolite, both single first order
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
Successfully compiled differential equation model from auto-generated C code.

+## Not run: ------------------------------------
+# # The above model used to be specified like this, before the advent of mkinsub()
+# SFO_SFO <- mkinmod(
+#   parent = list(type = "SFO", to = "m1"),
+#   m1 = list(type = "SFO"))
+# 
+# # Show details of creating the C function
+# SFO_SFO <- mkinmod(
+#   parent = mkinsub("SFO", "m1"),
+#   m1 = mkinsub("SFO"), verbose = TRUE)
+# 
+# # If we have several parallel metabolites 
+# # (compare tests/testthat/test_synthetic_data_for_UBA_2014.R)
+# m_synth_DFOP_par <- mkinmod(parent = mkinsub("DFOP", c("M1", "M2")),
+#                            M1 = mkinsub("SFO"),
+#                            M2 = mkinsub("SFO"),
+#                            use_of_ff = "max", quiet = TRUE)
+# 
+# fit_DFOP_par_c <- mkinfit(m_synth_DFOP_par, 
+#                           synthetic_data_for_UBA_2014[[12]]$data,
+#                           quiet = TRUE)
+## ---------------------------------------------
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinparplot.html b/docs/reference/mkinparplot.html new file mode 100644 index 00000000..f2fae22d --- /dev/null +++ b/docs/reference/mkinparplot.html @@ -0,0 +1,122 @@ + + + + + + + + +mkinparplot. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function plots the confidence intervals for the parameters + fitted using mkinfit.

+ + + 
mkinparplot(object)
+ +

Arguments

+
+
object
+
+ A fit represented in an mkinfit object. +
+
+ +
+

Value

+ +

Nothing is returned by this function, as it is called for its side effect, namely to produce a plot.

+
+ +

Examples

+ 
model <- mkinmod(
+  T245 = list(type = "SFO", to = c("phenol"), sink = FALSE),
+  phenol = list(type = "SFO", to = c("anisole")),
+  anisole = list(type = "SFO"), use_of_ff = "max")
Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE)
+mkinparplot(fit)
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinplot.html b/docs/reference/mkinplot.html new file mode 100644 index 00000000..51ca3992 --- /dev/null +++ b/docs/reference/mkinplot.html @@ -0,0 +1,118 @@ + + + + + + + + +mkinplot. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Deprecated function. It now only calls the plot method plot.mkinfit.

+ + + 
mkinplot(fit, ...)
+ +

Arguments

+
+
fit
+
+ an object of class mkinfit. +
+
&#8230;
+
+ further arguments passed to plot.mkinfit. +
+
+ +
+

Value

+ +

The function is called for its side effect.

+
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html new file mode 100644 index 00000000..730792c1 --- /dev/null +++ b/docs/reference/mkinpredict.html @@ -0,0 +1,318 @@ + + + + + + + + +mkinpredict. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function produces a time series for all the observed variables in a + kinetic model as specified by mkinmod, using a specific set of + kinetic parameters and initial values for the state variables.

+ + + 
mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve",
+              use_compiled = "auto", method.ode = "lsoda", atol = 1e-08, rtol = 1e-10,
+        map_output = TRUE, ...)
+ +

Arguments

+
+
mkinmod
+
+ A kinetic model as produced by mkinmod. +
+
odeparms
+
+ A numeric vector specifying the parameters used in the kinetic model, which + is generally defined as a set of ordinary differential equations. +
+
odeini
+
+ A numeric vectory containing the initial values of the state variables of + the model. Note that the state variables can differ from the observed + variables, for example in the case of the SFORB model. +
+
outtimes
+
+ A numeric vector specifying the time points for which model predictions + should be generated. +
+
solution_type
+
+ The method that should be used for producing the predictions. This should + generally be "analytical" if there is only one observed variable, and + usually "deSolve" in the case of several observed variables. The third + possibility "eigen" is faster but not applicable to some models e.g. + using FOMC for the parent compound. +
+
method.ode
+
+ The solution method passed via mkinpredict to + ode in case the solution type is "deSolve". The default + "lsoda" is performant, but sometimes fails to converge. +
+
use_compiled
+
+ If set to FALSE, no compiled version of the mkinmod + model is used, even if is present. +
+
atol
+
+ Absolute error tolerance, passed to ode. Default is 1e-8, + lower than in lsoda. +
+
rtol
+
+ Absolute error tolerance, passed to ode. Default is 1e-10, + much lower than in lsoda. +
+
map_output
+
+ Boolean to specify if the output should list values for the observed + variables (default) or for all state variables (if set to FALSE). +
+
&#8230;
+
+ Further arguments passed to the ode solver in case such a solver is used. +
+
+ +
+

Value

+ +

A matrix in the same format as the output of ode.

+
+ +

Examples

+ 
  SFO <- mkinmod(degradinol = list(type = "SFO"))
+  # Compare solution types
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              solution_type = "analytical")
#>    time  degradinol
+#> 1     0 100.0000000
+#> 2     1  74.0818221
+#> 3     2  54.8811636
+#> 4     3  40.6569660
+#> 5     4  30.1194212
+#> 6     5  22.3130160
+#> 7     6  16.5298888
+#> 8     7  12.2456428
+#> 9     8   9.0717953
+#> 10    9   6.7205513
+#> 11   10   4.9787068
+#> 12   11   3.6883167
+#> 13   12   2.7323722
+#> 14   13   2.0241911
+#> 15   14   1.4995577
+#> 16   15   1.1108997
+#> 17   16   0.8229747
+#> 18   17   0.6096747
+#> 19   18   0.4516581
+#> 20   19   0.3345965
+#> 21   20   0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              solution_type = "deSolve")
#>    time  degradinol
+#> 1     0 100.0000000
+#> 2     1  74.0818221
+#> 3     2  54.8811636
+#> 4     3  40.6569660
+#> 5     4  30.1194212
+#> 6     5  22.3130160
+#> 7     6  16.5298888
+#> 8     7  12.2456428
+#> 9     8   9.0717953
+#> 10    9   6.7205513
+#> 11   10   4.9787068
+#> 12   11   3.6883167
+#> 13   12   2.7323722
+#> 14   13   2.0241911
+#> 15   14   1.4995577
+#> 16   15   1.1108996
+#> 17   16   0.8229747
+#> 18   17   0.6096747
+#> 19   18   0.4516581
+#> 20   19   0.3345965
+#> 21   20   0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              solution_type = "deSolve", use_compiled = FALSE)
#>    time  degradinol
+#> 1     0 100.0000000
+#> 2     1  74.0818221
+#> 3     2  54.8811636
+#> 4     3  40.6569660
+#> 5     4  30.1194212
+#> 6     5  22.3130160
+#> 7     6  16.5298888
+#> 8     7  12.2456428
+#> 9     8   9.0717953
+#> 10    9   6.7205513
+#> 11   10   4.9787068
+#> 12   11   3.6883167
+#> 13   12   2.7323722
+#> 14   13   2.0241911
+#> 15   14   1.4995577
+#> 16   15   1.1108996
+#> 17   16   0.8229747
+#> 18   17   0.6096747
+#> 19   18   0.4516581
+#> 20   19   0.3345965
+#> 21   20   0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              solution_type = "eigen")
#>    time  degradinol
+#> 1     0 100.0000000
+#> 2     1  74.0818221
+#> 3     2  54.8811636
+#> 4     3  40.6569660
+#> 5     4  30.1194212
+#> 6     5  22.3130160
+#> 7     6  16.5298888
+#> 8     7  12.2456428
+#> 9     8   9.0717953
+#> 10    9   6.7205513
+#> 11   10   4.9787068
+#> 12   11   3.6883167
+#> 13   12   2.7323722
+#> 14   13   2.0241911
+#> 15   14   1.4995577
+#> 16   15   1.1108997
+#> 17   16   0.8229747
+#> 18   17   0.6096747
+#> 19   18   0.4516581
+#> 20   19   0.3345965
+#> 21   20   0.2478752
+#> 

+
+  # Compare integration methods to analytical solution
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              solution_type = "analytical")[21,]
#>    time degradinol
+#> 21   20  0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              method = "lsoda")[21,]
#>    time degradinol
+#> 21   20  0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              method = "ode45")[21,]
#>    time degradinol
+#> 21   20  0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
+              method = "rk4")[21,]
#>    time degradinol
+#> 21   20  0.2480043
+#> 
 # rk4 is not as precise here
+
+  # The number of output times used to make a lot of difference until the
+  # default for atol was adjusted
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
+              seq(0, 20, by = 0.1))[201,]
#>     time degradinol
+#> 201   20  0.2478752
+#> 
  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
+              seq(0, 20, by = 0.01))[2001,]
#>      time degradinol
+#> 2001   20  0.2478752
+#> 

+  # Check compiled model versions - they are faster than the eigenvalue based solutions!
+  SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
+                    m1 = list(type = "SFO"))
Successfully compiled differential equation model from auto-generated C code.
  system.time(
+    print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+                solution_type = "eigen")[201,]))
#>     time   parent       m1
+#> 201   20 4.978707 27.46227
+#> 
#>    user  system elapsed 
+#>   0.000   0.028   0.004 
+#> 
  system.time(
+    print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+                solution_type = "deSolve")[201,]))
#>     time   parent       m1
+#> 201   20 4.978707 27.46227
+#> 
#>    user  system elapsed 
+#>   0.016   0.004   0.002 
+#> 
  system.time(
+    print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
+                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
+                solution_type = "deSolve", use_compiled = FALSE)[201,]))
#>     time   parent       m1
+#> 201   20 4.978707 27.46227
+#> 
#>    user  system elapsed 
+#>   0.036   0.000   0.035 
+#>
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinresplot.html b/docs/reference/mkinresplot.html new file mode 100644 index 00000000..fb9ab40d --- /dev/null +++ b/docs/reference/mkinresplot.html @@ -0,0 +1,166 @@ + + + + + + + + +mkinresplot. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function plots the residuals for the specified subset of the + observed variables from an mkinfit object. A combined plot of the fitted + model and the residuals can be obtained using plot.mkinfit + using the argument show_residuals = TRUE.

+ + + 
mkinresplot(object,
+    obs_vars = names(object$mkinmod$map),
+    xlim = c(0, 1.1 * max(object$data$time)),
+    xlab = "Time", ylab = "Residual",
+    maxabs = "auto", legend = TRUE, lpos = "topright", ...)
+ +

Arguments

+
+
object
+
+ A fit represented in an mkinfit object. +
+
obs_vars
+
+ A character vector of names of the observed variables for which residuals + should be plotted. Defaults to all observed variables in the model +
+
xlim
+
+ plot range in x direction. +
+
xlab
+
+ Label for the x axis. Defaults to "Time [days]". +
+
ylab
+
+ Label for the y axis. Defaults to "Residual [% of applied radioactivity]". +
+
maxabs
+
+ Maximum absolute value of the residuals. This is used for the scaling of + the y axis and defaults to "auto". +
+
legend
+
+ Should a legend be plotted? Defaults to "TRUE". +
+
lpos
+
+ Where should the legend be placed? Default is "topright". Will be passed on to + legend.
+
&#8230;
+
+ further arguments passed to plot. +
+
+ +
+

Value

+ +

Nothing is returned by this function, as it is called for its side effect, namely to produce a plot.

+
+ +
+

See also

+ +

mkinplot, for a way to plot the data and the fitted lines of the + mkinfit object.

+
+ +

Examples

+ 
model <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(model, FOCUS_2006_D, quiet = TRUE)
+mkinresplot(fit, "m1")
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mkinsub.html b/docs/reference/mkinsub.html new file mode 100644 index 00000000..6b079c40 --- /dev/null +++ b/docs/reference/mkinsub.html @@ -0,0 +1,147 @@ + + + + + + + + +mkinsub. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This is a convenience function to set up the lists used as arguments for + mkinmod.

+ + + 
mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)
+ +

Arguments

+
+
submodel
+
+ Character vector of length one to specify the submodel type. See + mkinmod for the list of allowed submodel names. +
+
to
+
+ Vector of the names of the state variable to which a transformation + shall be included in the model. +
+
sink
+
+ Should a pathway to sink be included in the model in addition to the + pathways to other state variables? +
+
full_name
+
+ An optional name to be used e.g. for plotting fits performed with the model. + You can use non-ASCII characters here, but then your R code will not be + portable, i.e. may produce unintended plot results on other + operating systems or system configurations. +
+
+ +
+

Value

+ +

A list for use with mkinmod.

+
+ +

Examples

+ 
# One parent compound, one metabolite, both single first order.
+SFO_SFO <- mkinmod(
+  parent = list(type = "SFO", to = "m1"),
+  m1 = list(type = "SFO"))
Successfully compiled differential equation model from auto-generated C code.

+# The same model using mkinsub
+SFO_SFO.2 <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"))
Successfully compiled differential equation model from auto-generated C code.

+# Now supplying full names
+SFO_SFO.2 <- mkinmod(
+  parent = mkinsub("SFO", "m1", full_name = "Test compound"),
+  m1 = mkinsub("SFO", full_name = "Metabolite M1"))
Successfully compiled differential equation model from auto-generated C code.
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html new file mode 100644 index 00000000..5b624893 --- /dev/null +++ b/docs/reference/mmkin.html @@ -0,0 +1,178 @@ + + + + + + + + +mmkin. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This function calls mkinfit on all combinations of models and datasets + specified in its first two arguments.

+ + + 
mmkin(models, datasets,
+      cores = round(detectCores()/2), cluster = NULL, ...)
+ +

Arguments

+
+
models
+
+ Either a character vector of shorthand names ("SFO", "FOMC", "DFOP", + "HS", "SFORB"), or an optionally named list of mkinmod + objects. +
+
datasets
+
+ An optionally named list of datasets suitable as observed data for + mkinfit. +
+
cores
+
+ The number of cores to be used for multicore processing. This is only + used when the cluster argument is NULL. +
+
cluster
+
+ A cluster as returned by makeCluster to be used for parallel + execution. +
+
&#8230;
+
+ Further arguments that will be passed to mkinfit. +
+
+ +
+

Value

+ +

A matrix of mkinfit objects that can be indexed using the model + and dataset names as row and column indices.

+
+ +
+

See also

+ +

[.mmkin for subsetting, plot.mmkin for plotting.

+
+ +

Examples

+ 
## Not run: ------------------------------------
+# m_synth_SFO_lin <- mkinmod(parent = mkinsub("SFO", "M1"),
+#                            M1 = mkinsub("SFO", "M2"),
+#                            M2 = mkinsub("SFO"), use_of_ff = "max")
+# 
+# m_synth_FOMC_lin <- mkinmod(parent = mkinsub("FOMC", "M1"),
+#                             M1 = mkinsub("SFO", "M2"),
+#                             M2 = mkinsub("SFO"), use_of_ff = "max")
+# 
+# models <- list(SFO_lin = m_synth_SFO_lin, FOMC_lin = m_synth_FOMC_lin)
+# datasets <- lapply(synthetic_data_for_UBA_2014[1:3], function(x) x$data)
+# names(datasets) <- paste("Dataset", 1:3)
+# 
+# time_default <- system.time(fits.0 <- mmkin(models, datasets))
+# time_1 <- system.time(fits.1 <- mmkin(models, datasets, cores = 1))
+# 
+# time_default
+# time_1
+# 
+# endpoints(fits[["SFO_lin", 2]])
+# 
+# # Plot.mkinfit handles rows or columns of mmkin result objects
+# plot(fits.0[1, ])
+# plot(fits.0[1, ], obs_var = c("M1", "M2"))
+# plot(fits.0[, 1])
+# # Use double brackets to extract a single mkinfit object, which will be plotted
+# # by plot.mkinfit
+# plot(fits.0[[1, 1]], sep_obs = TRUE, show_residuals = TRUE, show_errmin = TRUE)
+# # Plotting with mmkin (single brackets, extracting an mmkin object) does not
+# # allow to plot the observed variables separately
+# plot(fits.0[1, 1])
+## ---------------------------------------------
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/plot.mkinfit.html b/docs/reference/plot.mkinfit.html new file mode 100644 index 00000000..94aebf63 --- /dev/null +++ b/docs/reference/plot.mkinfit.html @@ -0,0 +1,231 @@ + + + + + + + + +plot.mkinfit. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Solves the differential equations with the optimised and fixed parameters + from a previous successful call to mkinfit and plots + the observed data together with the solution of the fitted model.

+ + + 
# S3 method for mkinfit
+plot(x, fit = x,
+  obs_vars = names(fit$mkinmod$map),
+  xlab = "Time", ylab = "Observed", 
+  xlim = range(fit$data$time),
+  ylim = "default",
+  col_obs = 1:length(obs_vars), pch_obs = col_obs, 
+  lty_obs = rep(1, length(obs_vars)),
+  add = FALSE, legend = !add,
+  show_residuals = FALSE, maxabs = "auto",
+  sep_obs = FALSE, rel.height.middle = 0.9,
+  lpos = "topright", inset = c(0.05, 0.05), 
+  show_errmin = FALSE, errmin_digits = 3, …)
+plot_sep(fit, sep_obs = TRUE,  show_residuals = TRUE, show_errmin = TRUE, …)
+ +

Arguments

+
+
x
+
+ Alias for fit introduced for compatibility with the generic S3 method. +
+
fit
+
+ An object of class mkinfit. +
+
obs_vars
+
+ A character vector of names of the observed variables for which the + data and the model should be plotted. Defauls to all observed variables + in the model. +
+
xlab
+
+ Label for the x axis. +
+
ylab
+
+ Label for the y axis. +
+
xlim
+
+ Plot range in x direction. +
+
ylim
+
+ Plot range in y direction. +
+
col_obs
+
+ Colors used for plotting the observed data and the corresponding model prediction lines. +
+
pch_obs
+
+ Symbols to be used for plotting the data. +
+
lty_obs
+
+ Line types to be used for the model predictions. +
+
add
+
+ Should the plot be added to an existing plot? +
+
legend
+
+ Should a legend be added to the plot? +
+
show_residuals
+
+ Should residuals be shown? If only one plot of the fits is shown, the + residual plot is in the lower third of the plot? Otherwise, i.e. if + "sep_obs" is given, the residual plots will be located to the right of + the plots of the fitted curves. +
+
maxabs
+
+ Maximum absolute value of the residuals. This is used for the scaling of + the y axis and defaults to "auto". +
+
sep_obs
+
+ Should the observed variables be shown in separate subplots? If yes, residual plots + requested by "show_residuals" will be shown next to, not below the plot of the fits. +
+
rel.height.middle
+
+ The relative height of the middle plot, if more than two rows of plots are shown. +
+
lpos
+
+ Position(s) of the legend(s). Passed to legend as the first argument. + If not length one, this should be of the same length as the obs_var argument. +
+
inset
+
+ Passed to legend if applicable. +
+
show_errmin
+
+ Should the FOCUS chi2 error value be shown in the upper margin of the plot? +
+
errmin_digits
+
+ The number of significant digits for rounding the FOCUS chi2 error percentage. +
+
&#8230;
+
+ Further arguments passed to plot. +
+
+ +
+

Value

+ +

The function is called for its side effect.

+
+ +

Examples

+ 
# One parent compound, one metabolite, both single first order, path from
+# parent to sink included, use Levenberg-Marquardt for speed
+SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1", full = "Parent"),
+                   m1 = mkinsub("SFO", full = "Metabolite M1" ))
Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE, method.modFit = "Marq")
+plot(fit)
plot(fit, show_residuals = TRUE)

+# Show the observed variables separately
+plot(fit, sep_obs = TRUE, lpos = c("topright", "bottomright"))

+# Show the observed variables separately, with residuals
+plot(fit, sep_obs = TRUE, show_residuals = TRUE, lpos = c("topright", "bottomright"),
+     show_errmin = TRUE)

+# The same can be obtained with less typing, using the convenience function plot_sep
+plot_sep(fit, lpos = c("topright", "bottomright"))
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/plot.mmkin.html b/docs/reference/plot.mmkin.html new file mode 100644 index 00000000..358da679 --- /dev/null +++ b/docs/reference/plot.mmkin.html @@ -0,0 +1,156 @@ + + + + + + + + +plot.mmkin. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

When x is a row selected from an mmkin object ([.mmkin), the same model + fitted for at least one dataset is shown. When it is a column, the fit of at least one model + to the same dataset is shown.

+ + + 
# S3 method for mmkin
+plot(x, main = "auto", legends = 1, errmin_var = "All data", errmin_digits = 3,
+              cex = 0.7, rel.height.middle = 0.9, ...)
+ +

Arguments

+
+
x
+
+ An object of class mmkin, with either one row or one column. +
+
main
+
+ The main title placed on the outer margin of the plot. +
+
legends
+
+ An index for the fits for which legends should be shown. +
+
errmin_var
+
+ The variable for which the FOCUS chi2 error value should be shown. +
+
errmin_digits
+
+ The number of significant digits for rounding the FOCUS chi2 error percentage. +
+
cex
+
+ Passed to the plot functions and mtext. +
+
rel.height.middle
+
+ The relative height of the middle plot, if more than two rows of plots are shown. +
+
&#8230;
+
+ Further arguments passed to plot.mkinfit and mkinresplot. +
+
+ +
+

Value

+ +

The function is called for its side effect.

+
+ +

Examples

+ 
  # Only use one core not to offend CRAN checks, use Levenberg-Marquardt for speed
+  fits <- mmkin(c("FOMC", "HS"), list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C),
+                cores = 1, quiet = TRUE, method.modFit = "Marq")
+  plot(fits[, "FOCUS C"])
  plot(fits["FOMC", ])

+  # We can also plot a single fit, if we like the way mmkin works, but then the plot 
+  # height should be smaller than the plot width (this is not possible for the html pages
+  # generated by staticdocs, as far as I know).
+  plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/print.mkinds.html b/docs/reference/print.mkinds.html new file mode 100644 index 00000000..dea5f75c --- /dev/null +++ b/docs/reference/print.mkinds.html @@ -0,0 +1,109 @@ + + + + + + + + +print.mkinds. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Print mkinds objects.

+ + + 
# S3 method for mkinds
+print(x, ...)
+ +

Arguments

+
+
x
+
+ An mkinds object. +
+
&#8230;
+
+ Not used. +
+
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/print.mkinmod.html b/docs/reference/print.mkinmod.html new file mode 100644 index 00000000..38663f8f --- /dev/null +++ b/docs/reference/print.mkinmod.html @@ -0,0 +1,109 @@ + + + + + + + + +print.mkinmod. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Print mkinmod objects in a way that the user finds his way to get to its components.

+ + + 
# S3 method for mkinmod
+print(x, ...)
+ +

Arguments

+
+
x
+
+ An mkinmod object. +
+
&#8230;
+
+ Not used. +
+
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/schaefer07_complex_case.html b/docs/reference/schaefer07_complex_case.html new file mode 100644 index 00000000..12776c74 --- /dev/null +++ b/docs/reference/schaefer07_complex_case.html @@ -0,0 +1,131 @@ + + + + + + + + +schaefer07_complex_case. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

This dataset was used for a comparison of KinGUI and ModelMaker to check the + software quality of KinGUI in the original publication (Schäfer et al., 2007). + The results from the fitting are also included.

+ + + 
data(schaefer07_complex_case)
+ +
+

Format

+ +

The data set is a data frame with 8 observations on the following 6 variables. +

+
time
a numeric vector
+
parent
a numeric vector
+
A1
a numeric vector
+
B1
a numeric vector
+
C1
a numeric vector
+
A2
a numeric vector
+

+

The results are a data frame with 14 results for different parameter values

+
+ +
+

References

+ +

Schäfer D, Mikolasch B, Rainbird P and Harvey B (2007). KinGUI: a new kinetic + software tool for evaluations according to FOCUS degradation kinetics. In: Del + Re AAM, Capri E, Fragoulis G and Trevisan M (Eds.). Proceedings of the XIII + Symposium Pesticide Chemistry, Piacenza, 2007, p. 916-923.

+
+ +

Examples

+ 
data <- mkin_wide_to_long(schaefer07_complex_case, time = "time")
+model <- mkinmod(
+  parent = list(type = "SFO", to = c("A1", "B1", "C1"), sink = FALSE),
+  A1 = list(type = "SFO", to = "A2"),
+  B1 = list(type = "SFO"),
+  C1 = list(type = "SFO"),
+  A2 = list(type = "SFO"), use_of_ff = "max")
Successfully compiled differential equation model from auto-generated C code.
## Not run: mkinfit(model, data, plot=TRUE)
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html new file mode 100644 index 00000000..e0cdfe23 --- /dev/null +++ b/docs/reference/summary.mkinfit.html @@ -0,0 +1,229 @@ + + + + + + + + +summary.mkinfit. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

Lists model equations, the summary as returned by summary.modFit, + the chi2 error levels calculated according to FOCUS guidance (2006) as far + as defined therein, and optionally the data, consisting of observed, predicted + and residual values.

+ + + 
# S3 method for mkinfit
+summary(object, data = TRUE, distimes = TRUE, alpha = 0.05, ...)
+# S3 method for summary.mkinfit
+print(x, digits = max(3, getOption("digits") - 3), ...)
+ +

Arguments

+
+
object
+
+ an object of class mkinfit. +
+
x
+
+ an object of class summary.mkinfit. +
+
data
+
+ logical, indicating whether the data should be included in the summary. +
+
distimes
+
+ logical, indicating whether DT50 and DT90 values should be included. +
+
alpha
+
+ error level for confidence interval estimation from t distribution +
+
digits
+
+ Number of digits to use for printing +
+
&#8230;
+
+ optional arguments passed to methods like print. +
+
+ +
+

Value

+ +

The summary function returns a list derived from + summary.modFit, with components, among others

+

The print method is called for its side effect, i.e. printing the summary.

+
+ +
+

References

+ +

FOCUS (2006) “Guidance Document on Estimating Persistence and + Degradation Kinetics from Environmental Fate Studies on Pesticides in EU + Registration” Report of the FOCUS Work Group on Degradation Kinetics, + EC Document Reference Sanco/10058/2005 version 2.0, 434 pp, + http://focus.jrc.ec.europa.eu/dk

+
+ +

Examples

+ 
  summary(mkinfit(mkinmod(parent = list(type = "SFO")), FOCUS_2006_A, quiet = TRUE))
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.1 
+#> Date of fit:     Thu Oct  6 09:18:07 2016 
+#> Date of summary: Thu Oct  6 09:18:07 2016 
+#> 
+#> Equations:
+#> d_parent = - k_parent_sink * parent
+#> 
+#> Model predictions using solution type analytical 
+#> 
+#> Fitted with method Port using 35 model solutions performed in 0.079 s
+#> 
+#> Weighting: none
+#> 
+#> Starting values for parameters to be optimised:
+#>                value   type
+#> parent_0      101.24  state
+#> k_parent_sink   0.10 deparm
+#> 
+#> Starting values for the transformed parameters actually optimised:
+#>                        value lower upper
+#> parent_0          101.240000  -Inf   Inf
+#> log_k_parent_sink  -2.302585  -Inf   Inf
+#> 
+#> Fixed parameter values:
+#> None
+#> 
+#> Optimised, transformed parameters with symmetric confidence intervals:
+#>                   Estimate Std. Error  Lower   Upper
+#> parent_0           109.200     4.3910 98.410 119.900
+#> log_k_parent_sink   -3.291     0.1152 -3.573  -3.009
+#> 
+#> Parameter correlation:
+#>                   parent_0 log_k_parent_sink
+#> parent_0             1.000             0.575
+#> log_k_parent_sink    0.575             1.000
+#> 
+#> Residual standard error: 6.08 on 6 degrees of freedom
+#> 
+#> Backtransformed parameters:
+#> Confidence intervals for internally transformed parameters are asymmetric.
+#> t-test (unrealistically) based on the assumption of normal distribution
+#> for estimators of untransformed parameters.
+#>                Estimate t value    Pr(>t)    Lower     Upper
+#> parent_0      109.20000  24.860 1.394e-07 98.41000 119.90000
+#> k_parent_sink   0.03722   8.679 6.457e-05  0.02807   0.04934
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   8.385       2  6
+#> parent     8.385       2  6
+#> 
+#> Resulting formation fractions:
+#>             ff
+#> parent_sink  1
+#> 
+#> Estimated disappearance times:
+#>         DT50  DT90
+#> parent 18.62 61.87
+#> 
+#> Data:
+#>  time variable observed predicted residual
+#>     0   parent   101.24   109.153  -7.9132
+#>     3   parent    99.27    97.622   1.6484
+#>     7   parent    90.11    84.119   5.9913
+#>    14   parent    72.19    64.826   7.3641
+#>    30   parent    29.71    35.738  -6.0283
+#>    62   parent     5.98    10.862  -4.8818
+#>    90   parent     1.54     3.831  -2.2911
+#>   118   parent     0.39     1.351  -0.9613
+#>
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html new file mode 100644 index 00000000..04550199 --- /dev/null +++ b/docs/reference/synthetic_data_for_UBA.html @@ -0,0 +1,157 @@ + + + + + + + + +synthetic_data_for_UBA_2014. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

The 12 datasets were generated using four different models and three different + variance components. The four models are either the SFO or the DFOP model with either + two sequential or two parallel metabolites.

+ +

Variance component 'a' is based on a normal distribution with standard deviation of 3, + Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7. + Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the + minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07 + for the increase of the standard deviation with y.

+ +

Initial concentrations for metabolites and all values where adding the variance component resulted + in a value below the assumed limit of detection of 0.1 were set to NA.

+ +

As an example, the first dataset has the title SFO_lin_a and is based on the SFO model + with two sequential metabolites (linear pathway), with added variance component 'a'.

+ +

Compare also the code in the example section to see the degradation models.

+ + + 
synthetic_data_for_UBA_2014
+ +
+

Format

+ +

A list containing datasets in the form internally used by the 'gmkin' package. + The list has twelfe components. Each of the components is one dataset that has, + among others, the following components +

+
title
The name of the dataset, e.g. SFO_lin_a
+
data
A data frame with the data in the form expected by mkinfit
+

+
+ +
+

Source

+ +

Ranke (2014) Prüfung und Validierung von Modellierungssoftware als Alternative + zu ModelMaker 4.0, Umweltbundesamt Projektnummer 27452

+

Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for + measurement error in analytical chemistry. Technometrics 37(2), 176-184.

+
+ +

Examples

+ 
## Not run: ------------------------------------
+# m_synth_SFO_lin <- mkinmod(parent = list(type = "SFO", to = "M1"),
+#                            M1 = list(type = "SFO", to = "M2"),
+#                            M2 = list(type = "SFO"), use_of_ff = "max")
+# 
+# 
+# m_synth_SFO_par <- mkinmod(parent = list(type = "SFO", to = c("M1", "M2"),
+#                                          sink = FALSE),
+#                            M1 = list(type = "SFO"),
+#                            M2 = list(type = "SFO"), use_of_ff = "max")
+# 
+# m_synth_DFOP_lin <- mkinmod(parent = list(type = "DFOP", to = "M1"),
+#                             M1 = list(type = "SFO", to = "M2"),
+#                             M2 = list(type = "SFO"), use_of_ff = "max")
+# 
+# m_synth_DFOP_par <- mkinmod(parent = list(type = "DFOP", to = c("M1", "M2"),
+#                                           sink = FALSE),
+#                             M1 = list(type = "SFO"),
+#                             M2 = list(type = "SFO"), use_of_ff = "max")
+# 
+# mkinfit(m_synth_SFO_lin, synthetic_data_for_UBA_2014[[1]]$data)
+## ---------------------------------------------
+
+
+
+
+ + +
+ + + diff --git a/docs/reference/transform_odeparms.html b/docs/reference/transform_odeparms.html new file mode 100644 index 00000000..3b8be856 --- /dev/null +++ b/docs/reference/transform_odeparms.html @@ -0,0 +1,276 @@ + + + + + + + + +transform_odeparms. mkin + + + + + + + + + + + + + + + + + + + + + + + + +
+
+ + + +
+ +
+

+

+
+ +
+
+ +

The transformations are intended to map parameters that should only take + on restricted values to the full scale of real numbers. For kinetic rate + constants and other paramters that can only take on positive values, a + simple log transformation is used. For compositional parameters, such as + the formations fractions that should always sum up to 1 and can not be + negative, the ilr transformation is used.

+ +

The transformation of sets of formation fractions is fragile, as it supposes + the same ordering of the components in forward and backward transformation. + This is no problem for the internal use in mkinfit.

+ + + 
transform_odeparms(parms, mkinmod,
+                   transform_rates = TRUE, transform_fractions = TRUE)
+backtransform_odeparms(transparms, mkinmod,
+                       transform_rates = TRUE, transform_fractions = TRUE)
+ +

Arguments

+
+
parms
+
+ Parameters of kinetic models as used in the differential equations. +
+
transparms
+
+ Transformed parameters of kinetic models as used in the fitting procedure. +
+
mkinmod
+
+ The kinetic model of class mkinmod, containing the names of + the model variables that are needed for grouping the formation fractions + before ilr transformation, the parameter names and + the information if the pathway to sink is included in the model. +
+
transform_rates
+
+ Boolean specifying if kinetic rate constants should be transformed in the + model specification used in the fitting for better compliance with the + assumption of normal distribution of the estimator. If TRUE, also + alpha and beta parameters of the FOMC model are log-transformed, as well + as k1 and k2 rate constants for the DFOP and HS models and the break point tb + of the HS model. +
+
transform_fractions
+
+ Boolean specifying if formation fractions constants should be transformed in the + model specification used in the fitting for better compliance with the + assumption of normal distribution of the estimator. The default (TRUE) is + to do transformations. The g parameter of the DFOP and HS models are also + transformed, as they can also be seen as compositional data. The + transformation used for these transformations is the ilr + transformation. +
+
+ +
+

Value

+ +

A vector of transformed or backtransformed parameters with the same names + as the original parameters.

+
+ +

Examples

+ 
SFO_SFO <- mkinmod(
+  parent = list(type = "SFO", to = "m1", sink = TRUE),
+  m1 = list(type = "SFO"))
Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
+summary(fit, data=FALSE) # See transformed and backtransformed parameters
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.1 
+#> Date of fit:     Thu Oct  6 09:18:08 2016 
+#> Date of summary: Thu Oct  6 09:18:08 2016 
+#> 
+#> Equations:
+#> d_parent = - k_parent_sink * parent - k_parent_m1 * parent
+#> d_m1 = + k_parent_m1 * parent - k_m1_sink * m1
+#> 
+#> Model predictions using solution type deSolve 
+#> 
+#> Fitted with method Port using 153 model solutions performed in 0.636 s
+#> 
+#> Weighting: none
+#> 
+#> Starting values for parameters to be optimised:
+#>                  value   type
+#> parent_0      100.7500  state
+#> k_parent_sink   0.1000 deparm
+#> k_parent_m1     0.1001 deparm
+#> k_m1_sink       0.1002 deparm
+#> 
+#> Starting values for the transformed parameters actually optimised:
+#>                        value lower upper
+#> parent_0          100.750000  -Inf   Inf
+#> log_k_parent_sink  -2.302585  -Inf   Inf
+#> log_k_parent_m1    -2.301586  -Inf   Inf
+#> log_k_m1_sink      -2.300587  -Inf   Inf
+#> 
+#> Fixed parameter values:
+#>      value  type
+#> m1_0     0 state
+#> 
+#> Optimised, transformed parameters with symmetric confidence intervals:
+#>                   Estimate Std. Error  Lower   Upper
+#> parent_0            99.600    1.61400 96.330 102.900
+#> log_k_parent_sink   -3.038    0.07826 -3.197  -2.879
+#> log_k_parent_m1     -2.980    0.04124 -3.064  -2.897
+#> log_k_m1_sink       -5.248    0.13610 -5.523  -4.972
+#> 
+#> Parameter correlation:
+#>                   parent_0 log_k_parent_sink log_k_parent_m1 log_k_m1_sink
+#> parent_0           1.00000            0.6075        -0.06625       -0.1701
+#> log_k_parent_sink  0.60752            1.0000        -0.08740       -0.6253
+#> log_k_parent_m1   -0.06625           -0.0874         1.00000        0.4716
+#> log_k_m1_sink     -0.17006           -0.6253         0.47163        1.0000
+#> 
+#> Residual standard error: 3.211 on 36 degrees of freedom
+#> 
+#> Backtransformed parameters:
+#> Confidence intervals for internally transformed parameters are asymmetric.
+#> t-test (unrealistically) based on the assumption of normal distribution
+#> for estimators of untransformed parameters.
+#>                Estimate t value    Pr(>t)     Lower     Upper
+#> parent_0      99.600000  61.720 2.024e-38 96.330000 1.029e+02
+#> k_parent_sink  0.047920  12.780 3.050e-15  0.040890 5.616e-02
+#> k_parent_m1    0.050780  24.250 3.407e-24  0.046700 5.521e-02
+#> k_m1_sink      0.005261   7.349 5.758e-09  0.003992 6.933e-03
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   6.398       4 15
+#> parent     6.827       3  6
+#> m1         4.490       1  9
+#> 
+#> Resulting formation fractions:
+#>                 ff
+#> parent_sink 0.4855
+#> parent_m1   0.5145
+#> m1_sink     1.0000
+#> 
+#> Estimated disappearance times:
+#>           DT50   DT90
+#> parent   7.023  23.33
+#> m1     131.761 437.70
+#> 

+## Not run: ------------------------------------
+# fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE)
+# summary(fit.2, data=FALSE) 
+## ---------------------------------------------
+
+initials <- fit$start$value
+names(initials) <- rownames(fit$start)
+transformed <- fit$start_transformed$value
+names(transformed) <- rownames(fit$start_transformed)
+transform_odeparms(initials, SFO_SFO)
#>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
+#>        100.750000         -2.302585         -2.301586         -2.300587 
+#> 
backtransform_odeparms(transformed, SFO_SFO)
#>      parent_0 k_parent_sink   k_parent_m1     k_m1_sink 
+#>      100.7500        0.1000        0.1001        0.1002 
+#> 

+## Not run: ------------------------------------
+# # The case of formation fractions
+# SFO_SFO.ff <- mkinmod(
+#   parent = list(type = "SFO", to = "m1", sink = TRUE),
+#   m1 = list(type = "SFO"),
+#   use_of_ff = "max")
+# 
+# fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D)
+# summary(fit.ff, data = FALSE)
+# initials <- c("f_parent_to_m1" = 0.5)
+# transformed <- transform_odeparms(initials, SFO_SFO.ff)
+# backtransform_odeparms(transformed, SFO_SFO.ff)
+# 
+# # And without sink
+# SFO_SFO.ff.2 <- mkinmod(
+#   parent = list(type = "SFO", to = "m1", sink = FALSE),
+#   m1 = list(type = "SFO"),
+#   use_of_ff = "max")
+# 
+# 
+# fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D)
+# summary(fit.ff.2, data = FALSE)
+## ---------------------------------------------
+
+
+

Author

+ + Johannes Ranke + +
+
+ + +
+ + + diff --git a/docs/reference/unknown-10.png b/docs/reference/unknown-10.png new file mode 100644 index 00000000..09bb687c Binary files /dev/null and b/docs/reference/unknown-10.png differ diff --git a/docs/reference/unknown-2.png b/docs/reference/unknown-2.png new file mode 100644 index 00000000..a26e413f Binary files /dev/null and b/docs/reference/unknown-2.png differ diff --git a/docs/reference/unknown-4.png b/docs/reference/unknown-4.png new file mode 100644 index 00000000..f23ed172 Binary files /dev/null and b/docs/reference/unknown-4.png differ diff --git a/docs/reference/unknown-6.png b/docs/reference/unknown-6.png new file mode 100644 index 00000000..dc24d92f Binary files /dev/null and b/docs/reference/unknown-6.png differ diff --git a/docs/reference/unknown-8.png b/docs/reference/unknown-8.png new file mode 100644 index 00000000..e4ab674a Binary files /dev/null and b/docs/reference/unknown-8.png differ -- cgit v1.2.1