From 3eefecf0adfbb30b8fb895c244dea6903bcb3e9c Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 31 Jan 2019 16:55:20 +0100 Subject: Restore NAMESPACE which was accidentally overwritten by pkgdown -> roxygen --- NAMESPACE | 32 +- R/mkinds.R | 17 +- docs/articles/FOCUS_D.html | 14 +- docs/articles/FOCUS_L.html | 40 +- docs/articles/web_only/compiled_models.html | 10 +- docs/reference/AIC.mmkin.html | 16 +- docs/reference/DFOP.solution.html | 2 +- docs/reference/Extract.mmkin.html | 402 +++++++++++- docs/reference/FOMC.solution.html | 2 +- docs/reference/HS.solution.html | 2 +- docs/reference/IORE.solution.html | 15 +- docs/reference/SFO.solution.html | 2 +- docs/reference/SFORB.solution.html | 2 +- docs/reference/add_err.html | 20 +- docs/reference/endpoints.html | 12 +- docs/reference/geometric_mean.html | 2 +- docs/reference/ilr.html | 15 +- docs/reference/logLik.mkinfit.html | 14 +- docs/reference/max_twa_parent.html | 4 +- docs/reference/mccall81_245T.html | 183 +++++- docs/reference/mkin_long_to_wide.html | 24 +- docs/reference/mkin_wide_to_long.html | 8 +- docs/reference/mkinerrmin.html | 12 +- docs/reference/mkinfit.html | 906 +++++++++++++++++++++++++++- docs/reference/mkinmod.html | 35 +- docs/reference/mkinparplot.html | 3 +- docs/reference/mkinpredict.html | 165 ++++- docs/reference/mkinresplot.html | 3 +- docs/reference/mkinsub.html | 6 +- docs/reference/mmkin.html | 36 +- docs/reference/plot.mkinfit.html | 9 +- docs/reference/plot.mmkin.html | 5 +- docs/reference/print.mkinmod.html | 18 +- docs/reference/schaefer07_complex_case.html | 20 +- docs/reference/summary.mkinfit.html | 71 ++- docs/reference/test_data_from_UBA_2014.html | 48 +- docs/reference/transform_odeparms.html | 316 +++++++++- inst/examples/mkinds.R | 1 - vignettes/FOCUS_D.Rmd | 11 +- vignettes/FOCUS_D.html | 438 ++++++++++++-- 40 files changed, 2710 insertions(+), 231 deletions(-) delete mode 100644 inst/examples/mkinds.R diff --git a/NAMESPACE b/NAMESPACE index 3286b2b8..fc812f46 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,5 +1,29 @@ -# Generated by roxygen2: do not edit by hand +# Export all names +exportPattern("^[^\\.]") +S3method(print, mkinds) +S3method(print, mkinmod) +S3method(plot, mkinfit) +S3method(summary, mkinfit) +S3method(print, summary.mkinfit) +S3method(logLik, mkinfit) +S3method(plot, mmkin) +S3method("[", mmkin) +S3method(AIC, mmkin) +S3method(mkinpredict, mkinmod) +S3method(mkinpredict, mkinfit) -S3method(print,mkinds) -export(mkinds) -importFrom(R6,R6Class) +import( + stats, + graphics, + FME, + minpack.lm, + rootSolve, + inline, + parallel +) +importFrom(deSolve, ode) +importFrom(methods, signature) +importFrom(R6, R6Class) +importFrom(grDevices, dev.cur) +importFrom(plyr, join) +importFrom(utils, write.table) diff --git a/R/mkinds.R b/R/mkinds.R index bed49be3..257a17c4 100644 --- a/R/mkinds.R +++ b/R/mkinds.R @@ -1,4 +1,4 @@ -# Copyright (C) 2015,2018 Johannes Ranke +# Copyright (C) 2015,2018,2019 Johannes Ranke # Contact: jranke@uni-bremen.de # This file is part of the R package mkin @@ -16,21 +16,6 @@ # You should have received a copy of the GNU General Public License along with # this program. If not, see -#' A dataset class for mkin -#' -#' @docType class -#' @importFrom R6 R6Class -#' @export -#' @format An \code{\link{R6Class}} generator object. -#' @field title A full title for the dataset -#' @field sampling times The sampling times -#' @field time_unit The time unit -#' @field observed Names of the observed compounds -#' @field unit The unit of the observations -#' @field replicates The number of replicates -#' @field data A dataframe with at least the columns name, time and value -#' in order to be compatible with mkinfit -#' @example inst/examples/mkinds.R mkinds <- R6Class("mkinds", public = list( title = NULL, diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index deab980c..9acab53a 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -94,8 +94,8 @@ -

This is just a very simple vignette showing how to fit a degradation model for a parent compound with one transformation product using mkin. After loading the library we look a the data. We have observed concentrations in the column named value at the times specified in column time for the two observed variables named parent and m1.

-
library("mkin", quietly = TRUE)
+
This is just a very simple vignette showing how to fit a degradation model for a parent compound with one transformation product using mkin. After loading the library we look at the data. We have observed concentrations in the column named value at the times specified in column time for the two observed variables named parent and m1.

+
library(mkin, quietly = TRUE)
 print(FOCUS_2006_D)

 
##      name time  value
 ## 1  parent    0  99.46
@@ -161,10 +161,10 @@
 

 
A comprehensive report of the results is obtained using the summary method for mkinfit objects.

 
summary(fit)

-
## mkin version used for fitting:    0.9.47.6 
-## R version used for fitting:       3.5.1 
-## Date of fit:     Fri Nov 23 19:58:46 2018 
-## Date of summary: Fri Nov 23 19:58:47 2018 
+
## mkin version used for fitting:    0.9.47.5 
+## R version used for fitting:       3.5.2 
+## Date of fit:     Thu Jan 31 16:52:37 2019 
+## Date of summary: Thu Jan 31 16:52:38 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -172,7 +172,7 @@
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 0.736 s
+## Fitted with method Port using 153 model solutions performed in 0.695 s
 ## 
 ## Weighting: none
 ## 
diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html
index b53ab0d0..e3ca9aff 100644
--- a/docs/articles/FOCUS_L.html
+++ b/docs/articles/FOCUS_L.html
@@ -111,8 +111,8 @@
 summary(m.L1.SFO)
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:40 2019 
-## Date of summary: Thu Jan 31 15:43:40 2019 
+## Date of fit:     Thu Jan 31 16:52:39 2019 
+## Date of summary: Thu Jan 31 16:52:39 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
@@ -202,15 +202,15 @@
 
summary(m.L1.FOMC, data = FALSE)

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:42 2019 
-## Date of summary: Thu Jan 31 15:43:42 2019 
+## Date of fit:     Thu Jan 31 16:52:41 2019 
+## Date of summary: Thu Jan 31 16:52:41 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 611 model solutions performed in 1.502 s
+## Fitted with method Port using 611 model solutions performed in 1.49 s
 ## 
 ## Weighting: none
 ## 
@@ -297,15 +297,15 @@
 
summary(m.L2.FOMC, data = FALSE)

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:42 2019 
-## Date of summary: Thu Jan 31 15:43:42 2019 
+## Date of fit:     Thu Jan 31 16:52:42 2019 
+## Date of summary: Thu Jan 31 16:52:42 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 81 model solutions performed in 0.195 s
+## Fitted with method Port using 81 model solutions performed in 0.198 s
 ## 
 ## Weighting: none
 ## 
@@ -368,8 +368,8 @@
 
summary(m.L2.DFOP, data = FALSE)

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:43 2019 
-## Date of summary: Thu Jan 31 15:43:43 2019 
+## Date of fit:     Thu Jan 31 16:52:43 2019 
+## Date of summary: Thu Jan 31 16:52:43 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -378,7 +378,7 @@
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 336 model solutions performed in 0.836 s
+## Fitted with method Port using 336 model solutions performed in 0.839 s
 ## 
 ## Weighting: none
 ## 
@@ -460,8 +460,8 @@
 
summary(mm.L3[["DFOP", 1]])

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:44 2019 
-## Date of summary: Thu Jan 31 15:43:45 2019 
+## Date of fit:     Thu Jan 31 16:52:44 2019 
+## Date of summary: Thu Jan 31 16:52:44 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -470,7 +470,7 @@
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 137 model solutions performed in 0.34 s
+## Fitted with method Port using 137 model solutions performed in 0.341 s
 ## 
 ## Weighting: none
 ## 
@@ -561,15 +561,15 @@
 
summary(mm.L4[["SFO", 1]], data = FALSE)

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:45 2019 
-## Date of summary: Thu Jan 31 15:43:45 2019 
+## Date of fit:     Thu Jan 31 16:52:44 2019 
+## Date of summary: Thu Jan 31 16:52:45 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.109 s
+## Fitted with method Port using 46 model solutions performed in 0.11 s
 ## 
 ## Weighting: none
 ## 
@@ -621,15 +621,15 @@
 
summary(mm.L4[["FOMC", 1]], data = FALSE)

 
## mkin version used for fitting:    0.9.47.5 
 ## R version used for fitting:       3.5.2 
-## Date of fit:     Thu Jan 31 15:43:45 2019 
-## Date of summary: Thu Jan 31 15:43:45 2019 
+## Date of fit:     Thu Jan 31 16:52:45 2019 
+## Date of summary: Thu Jan 31 16:52:45 2019 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 66 model solutions performed in 0.163 s
+## Fitted with method Port using 66 model solutions performed in 0.162 s
 ## 
 ## Weighting: none
 ## 
diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html
index d7d76b49..08bb9b44 100644
--- a/docs/articles/web_only/compiled_models.html
+++ b/docs/articles/web_only/compiled_models.html
@@ -126,9 +126,9 @@
 }

 
## Lade nötiges Paket: rbenchmark

 
##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   2.331    1.000     2.330        0
-## 1 deSolve, not compiled            3  17.369    7.451    17.360        0
-## 2      Eigenvalue based            3   2.878    1.235     2.876        0
+## 3     deSolve, compiled            3   2.353    1.000     2.352        0
+## 1 deSolve, not compiled            3  17.619    7.488    17.609        0
+## 2      Eigenvalue based            3   2.899    1.232     2.898        0
 ##   user.child sys.child
 ## 3          0         0
 ## 1          0         0
@@ -157,8 +157,8 @@
 }

 
## Successfully compiled differential equation model from auto-generated C code.

 
##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   4.120    1.000     4.116        0
-## 1 deSolve, not compiled            3  37.011    8.983    36.993        0
+## 2     deSolve, compiled            3   4.180    1.000     4.177        0
+## 1 deSolve, not compiled            3  37.331    8.931    37.312        0
 ##   user.child sys.child
 ## 2          0         0
 ## 1          0         0

diff --git a/docs/reference/AIC.mmkin.html b/docs/reference/AIC.mmkin.html
index a90e81bb..d90b325f 100644
--- a/docs/reference/AIC.mmkin.html
+++ b/docs/reference/AIC.mmkin.html
@@ -160,12 +160,22 @@
     
Examples

     
  f <- mmkin(c("SFO", "FOMC", "DFOP"),
     list("FOCUS A" = FOCUS_2006_A,
-         "FOCUS C" = FOCUS_2006_C))
#> Error in mmkin(c("SFO", "FOMC", "DFOP"), list(`FOCUS A` = FOCUS_2006_A,     `FOCUS C` = FOCUS_2006_C)): konnte Funktion "mmkin" nicht finden
  AIC(f[1, "FOCUS A"]) # We get a single number for a single fit
#> Error in AIC(f[1, "FOCUS A"]): Objekt 'f' nicht gefunden

+         "FOCUS C" = FOCUS_2006_C))
+  AIC(f[1, "FOCUS A"]) # We get a single number for a single fit
#> [1] 55.32452

   # For FOCUS A, the models fit almost equally well, so the higher the number
   # of parameters, the higher (worse) the AIC
-  AIC(f[, "FOCUS A"])
#> Error in AIC(f[, "FOCUS A"]): Objekt 'f' nicht gefunden
  AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
#> Error in AIC(f[, "FOCUS A"], k = 0): Objekt 'f' nicht gefunden

+  AIC(f[, "FOCUS A"])
#>      df      AIC
+#> SFO   3 55.32452
+#> FOMC  4 57.32477
+#> DFOP  5 59.32452
  AIC(f[, "FOCUS A"], k = 0) # If we do not penalize additional parameters, we get nearly the same
#>      df      AIC
+#> SFO   3 49.32452
+#> FOMC  4 49.32477
+#> DFOP  5 49.32452

   # For FOCUS C, the more complex models fit better
-  AIC(f[, "FOCUS C"])
#> Error in AIC(f[, "FOCUS C"]): Objekt 'f' nicht gefunden

+  AIC(f[, "FOCUS C"])
#>      df      AIC
+#> SFO   3 59.84675
+#> FOMC  4 44.70584
+#> DFOP  5 29.08369

   
   
   
#> [[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 verstrichen 
+#>       0.197       0.000       0.198 
+#> 
+#> $mkinmod
+#> <mkinmod> model generated with
+#> Use of formation fractions $use_of_ff: min 
+#> Specification $spec:
+#> $parent
+#> $type: SFO; $sink: TRUE
+#> Coefficient matrix $coefmat available
+#> Differential equations:
+#> d_parent/dt = - k_parent_sink * parent
+#> 
+#> $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)
+#> }
+#> <bytecode: 0x55555916c520>
+#> <environment: 0x55555b68a808>
+#> 
+#> $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)
+#> }
+#> <bytecode: 0x55555a1242b0>
+#> <environment: 0x55555b68a808>
+#> 
+#> $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 Zeilen> (oder row.names mit Länge 0)
+#> 
+#> $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"
+#> 
+#> $tc.ini
+#> sigma_low  rsd_high 
+#>      0.50      0.07 
+#> 
+#> $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 Jan 31 16:50:45 2019"
+#> 
+#> $version
+#> [1] "0.9.47.6"
+#> 
+#> $Rversion
+#> [1] "3.5.2"
+#> 
+#> attr(,"class")
+#> [1] "mkinfit" "modFit" 
+#> 

   
   
   
   
#>             coef.fit.fomc. coef.fit.iore. coef.fit.iore.deS.
+#> model par 1    85.87489063      85.874890          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

   
   
   
   
   
   
   
#> [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

   
   
#>       df      AIC
+#> f_nw   5 204.4619
+#> f_obs  6 205.8727
+#> f_tc   6 143.8773
+#> f_man  4 291.8000

   
   
   
#> mkin version used for fitting:    0.9.47.6 
+#> R version used for fitting:       3.5.2 
+#> Date of fit:     Thu Jan 31 16:51:07 2019 
+#> Date of summary: Thu Jan 31 16:51:07 2019 
+#> 
+#> Equations:
+#> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
+#> d_phenol/dt = + k_T245_phenol * T245 - k_phenol_sink * phenol -
+#>            k_phenol_anisole * phenol
+#> d_anisole/dt = + k_phenol_anisole * phenol - k_anisole_sink * anisole
+#> 
+#> Model predictions using solution type deSolve 
+#> 
+#> Fitted with method Port using 246 model solutions performed in 1.618 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
#> 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
#> 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
#> mkin version used for fitting: 0.9.47.6 +#> R version used for fitting: 3.5.2 +#> Date of fit: Thu Jan 31 16:51:28 2019 +#> Date of summary: Thu Jan 31 16:51:28 2019 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 270 model solutions performed in 1.257 s +#> +#> Weighting: manual +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -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 99.49000 1.33200 96.7800 102.2000 +#> log_k_parent -2.32100 0.03550 -2.3930 -2.2490 +#> log_k_m1 -5.24100 0.21280 -5.6730 -4.8100 +#> f_parent_ilr_1 0.04571 0.08966 -0.1361 0.2275 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.00000 0.5312 -0.09456 -0.3351 +#> log_k_parent 0.53123 1.0000 -0.17800 -0.3360 +#> log_k_m1 -0.09456 -0.1780 1.00000 0.7616 +#> f_parent_ilr_1 -0.33514 -0.3360 0.76156 1.0000 +#> +#> Residual standard error: 2.628 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 99.490000 74.69 2.221e-41 96.780000 1.022e+02 +#> k_parent 0.098140 28.17 2.012e-26 0.091320 1.055e-01 +#> k_m1 0.005292 4.70 1.873e-05 0.003437 8.148e-03 +#> f_parent_to_m1 0.516200 16.30 1.686e-18 0.452000 5.798e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.400 4 15 +#> parent 6.454 2 7 +#> m1 4.708 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5162 +#> parent_sink 0.4838 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 7.063 23.46 +#> m1 130.971 435.08 +#> +#> Data: +#> time variable observed predicted residual err +#> 0 parent 99.46 99.48598 -0.025979 1 +#> 0 parent 102.04 99.48598 2.554021 1 +#> 1 parent 93.50 90.18612 3.313880 1 +#> 1 parent 92.50 90.18612 2.313880 1 +#> 3 parent 63.23 74.11316 -10.883163 1 +#> 3 parent 68.99 74.11316 -5.123163 1 +#> 7 parent 52.32 50.05030 2.269705 1 +#> 7 parent 55.13 50.05030 5.079705 1 +#> 14 parent 27.27 25.17975 2.090250 1 +#> 14 parent 26.64 25.17975 1.460250 1 +#> 21 parent 11.50 12.66765 -1.167654 1 +#> 21 parent 11.64 12.66765 -1.027654 1 +#> 35 parent 2.85 3.20616 -0.356164 1 +#> 35 parent 2.91 3.20616 -0.296164 1 +#> 50 parent 0.69 0.73562 -0.045619 1 +#> 50 parent 0.63 0.73562 -0.105619 1 +#> 75 parent 0.05 0.06326 -0.013256 1 +#> 75 parent 0.06 0.06326 -0.003256 1 +#> 0 m1 0.00 0.00000 0.000000 2 +#> 0 m1 0.00 0.00000 0.000000 2 +#> 1 m1 4.84 4.78729 0.052713 2 +#> 1 m1 5.64 4.78729 0.852713 2 +#> 3 m1 12.91 12.98785 -0.077848 2 +#> 3 m1 12.96 12.98785 -0.027848 2 +#> 7 m1 22.97 24.99695 -2.026946 2 +#> 7 m1 24.47 24.99695 -0.526946 2 +#> 14 m1 41.69 36.66353 5.026472 2 +#> 14 m1 33.21 36.66353 -3.453528 2 +#> 21 m1 44.37 41.65681 2.713186 2 +#> 21 m1 46.44 41.65681 4.783186 2 +#> 35 m1 41.22 43.35031 -2.130314 2 +#> 35 m1 37.95 43.35031 -5.400314 2 +#> 50 m1 41.19 41.25637 -0.066368 2 +#> 50 m1 40.01 41.25637 -1.246368 2 +#> 75 m1 40.09 36.46057 3.629429 2 +#> 75 m1 33.85 36.46057 -2.610571 2 +#> 100 m1 31.04 31.96929 -0.929293 2 +#> 100 m1 33.13 31.96929 1.160707 2 +#> 120 m1 25.15 28.76062 -3.610621 2 +#> 120 m1 33.31 28.76062 4.549379 2
f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man", quiet = TRUE, + reweight.method = "obs") +summary(f.w.man.irls)
#> mkin version used for fitting: 0.9.47.6 +#> R version used for fitting: 3.5.2 +#> Date of fit: Thu Jan 31 16:51:31 2019 +#> Date of summary: Thu Jan 31 16:51:31 2019 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + f_parent_to_m1 * k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 692 model solutions performed in 3.3 s +#> +#> Weighting: manual +#> +#> Iterative reweighting with method obs +#> Final mean squared residuals of observed variables: +#> parent m1 +#> 11.573406 7.407846 +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> f_parent_to_m1 0.5000 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -Inf Inf +#> f_parent_ilr_1 0.000000 -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 99.67000 1.79200 96.04000 103.300 +#> log_k_parent -2.31200 0.04560 -2.40400 -2.220 +#> log_k_m1 -5.25100 0.12510 -5.50500 -4.998 +#> f_parent_ilr_1 0.03785 0.06318 -0.09027 0.166 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5083 -0.1979 -0.6148 +#> log_k_parent 0.5083 1.0000 -0.3894 -0.6062 +#> log_k_m1 -0.1979 -0.3894 1.0000 0.7417 +#> f_parent_ilr_1 -0.6148 -0.6062 0.7417 1.0000 +#> +#> Residual standard error: 1.054 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 99.67000 55.630 8.185e-37 96.040000 1.033e+02 +#> k_parent 0.09906 21.930 1.016e-22 0.090310 1.087e-01 +#> k_m1 0.00524 7.996 8.486e-10 0.004066 6.753e-03 +#> f_parent_to_m1 0.51340 23.000 2.039e-23 0.468100 5.584e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.399 4 15 +#> parent 6.466 2 7 +#> m1 4.679 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5134 +#> parent_sink 0.4866 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 6.997 23.24 +#> m1 132.282 439.43 +#> +#> Data: +#> time variable observed predicted residual err.ini err +#> 0 parent 99.46 99.67217 -2.122e-01 1 3.402 +#> 0 parent 102.04 99.67217 2.368e+00 1 3.402 +#> 1 parent 93.50 90.27152 3.228e+00 1 3.402 +#> 1 parent 92.50 90.27152 2.228e+00 1 3.402 +#> 3 parent 63.23 74.04648 -1.082e+01 1 3.402 +#> 3 parent 68.99 74.04648 -5.056e+00 1 3.402 +#> 7 parent 52.32 49.82092 2.499e+00 1 3.402 +#> 7 parent 55.13 49.82092 5.309e+00 1 3.402 +#> 14 parent 27.27 24.90288 2.367e+00 1 3.402 +#> 14 parent 26.64 24.90288 1.737e+00 1 3.402 +#> 21 parent 11.50 12.44765 -9.477e-01 1 3.402 +#> 21 parent 11.64 12.44765 -8.077e-01 1 3.402 +#> 35 parent 2.85 3.11002 -2.600e-01 1 3.402 +#> 35 parent 2.91 3.11002 -2.000e-01 1 3.402 +#> 50 parent 0.69 0.70375 -1.375e-02 1 3.402 +#> 50 parent 0.63 0.70375 -7.375e-02 1 3.402 +#> 75 parent 0.05 0.05913 -9.134e-03 1 3.402 +#> 75 parent 0.06 0.05913 8.661e-04 1 3.402 +#> 0 m1 0.00 0.00000 0.000e+00 2 2.722 +#> 0 m1 0.00 0.00000 0.000e+00 2 2.722 +#> 1 m1 4.84 4.81328 2.672e-02 2 2.722 +#> 1 m1 5.64 4.81328 8.267e-01 2 2.722 +#> 3 m1 12.91 13.04779 -1.378e-01 2 2.722 +#> 3 m1 12.96 13.04779 -8.779e-02 2 2.722 +#> 7 m1 22.97 25.07615 -2.106e+00 2 2.722 +#> 7 m1 24.47 25.07615 -6.062e-01 2 2.722 +#> 14 m1 41.69 36.70729 4.983e+00 2 2.722 +#> 14 m1 33.21 36.70729 -3.497e+00 2 2.722 +#> 21 m1 44.37 41.65050 2.719e+00 2 2.722 +#> 21 m1 46.44 41.65050 4.789e+00 2 2.722 +#> 35 m1 41.22 43.28866 -2.069e+00 2 2.722 +#> 35 m1 37.95 43.28866 -5.339e+00 2 2.722 +#> 50 m1 41.19 41.19339 -3.387e-03 2 2.722 +#> 50 m1 40.01 41.19339 -1.183e+00 2 2.722 +#> 75 m1 40.09 36.43820 3.652e+00 2 2.722 +#> 75 m1 33.85 36.43820 -2.588e+00 2 2.722 +#> 100 m1 31.04 31.98971 -9.497e-01 2 2.722 +#> 100 m1 33.13 31.98971 1.140e+00 2 2.722 +#> 120 m1 25.15 28.80897 -3.659e+00 2 2.722 +#> 120 m1 33.31 28.80897 4.501e+00 2 2.722
#> Successfully compiled differential equation model from auto-generated C code.
fit <- mkinfit(model, subset(mccall81_245T, soil == "Commerce"), quiet = TRUE) +mkinparplot(fit)
#> Successfully compiled differential equation model from auto-generated C code.
#> Successfully compiled differential equation model from auto-generated C code.
+ print(m_synth_SFO_lin)
#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: max +#> Specification $spec: +#> $parent +#> $type: SFO; $to: M1; $sink: TRUE +#> $M1 +#> $type: SFO; $to: M2; $sink: TRUE +#> $M2 +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> Compiled model $cf available +#> Differential equations: +#> d_parent/dt = - k_parent * parent +#> d_M1/dt = + f_parent_to_M1 * k_parent * parent - k_M1 * M1 +#> d_M2/dt = + f_M1_to_M2 * k_M1 * M1 - k_M2 * M2
#> Successfully compiled differential equation model from auto-generated C code.
+ +fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D, quiet = TRUE) +summary(fit.ff.2, data = FALSE)
#> mkin version used for fitting: 0.9.47.6 +#> R version used for fitting: 3.5.2 +#> Date of fit: Thu Jan 31 16:52:35 2019 +#> Date of summary: Thu Jan 31 16:52:35 2019 +#> +#> Equations: +#> d_parent/dt = - k_parent * parent +#> d_m1/dt = + k_parent * parent - k_m1 * m1 +#> +#> Model predictions using solution type deSolve +#> +#> Fitted with method Port using 104 model solutions performed in 0.482 s +#> +#> Weighting: none +#> +#> Starting values for parameters to be optimised: +#> value type +#> parent_0 100.7500 state +#> k_parent 0.1000 deparm +#> k_m1 0.1001 deparm +#> +#> Starting values for the transformed parameters actually optimised: +#> value lower upper +#> parent_0 100.750000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_m1 -2.301586 -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 84.790 2.96500 78.78 90.800 +#> log_k_parent -2.756 0.08088 -2.92 -2.593 +#> log_k_m1 -4.214 0.11150 -4.44 -3.988 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 +#> parent_0 1.0000 0.11058 0.46156 +#> log_k_parent 0.1106 1.00000 0.06274 +#> log_k_m1 0.4616 0.06274 1.00000 +#> +#> Residual standard error: 8.333 on 37 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 84.79000 28.600 3.939e-27 78.78000 90.80000 +#> k_parent 0.06352 12.360 5.237e-15 0.05392 0.07483 +#> k_m1 0.01478 8.966 4.114e-11 0.01179 0.01853 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 19.66 3 16 +#> parent 17.56 2 7 +#> m1 18.71 1 9 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 10.91 36.25 +#> m1 46.89 155.75