From c6086d1dd97ad2d6420625de7b8009b1b0f85d06 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Fri, 18 Nov 2016 15:01:53 +0100 Subject: Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE) Using branch 'jranke' on jranke/pkgdown, fixing issues hadley/pgkdown#178 and hadley/pkgdown#213 Remove plot=TRUE from mkinfit calls also in dontrun sections of examples to avoid a flood png files documenting the progress of the fit. --- GNUmakefile | 4 +- _pkgdown.yml | 4 +- docs/articles/FOCUS_D.html | 2 +- docs/articles/FOCUS_D_cache/html/__packages | 2 - .../plot_2_a17fdb1fd55c48e44fecf3303fab9127.RData | Bin 0 -> 2756 bytes .../plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdb | 0 .../plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdx | Bin 0 -> 113 bytes .../plot_7ea6a8e7d5684cd6a8daf57a478ef419.RData | Bin 0 -> 2786 bytes .../html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdb | 0 .../html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdx | Bin 0 -> 113 bytes docs/articles/FOCUS_D_files/figure-html/plot-1.png | Bin 95834 -> 38557 bytes .../FOCUS_D_files/figure-html/plot_2-1.png | Bin 14059 -> 6091 bytes docs/articles/FOCUS_L.html | 44 +- docs/articles/compiled_models.html | 28 +- .../figure-html/benchmark_FOMC_SFO-1.png | Bin 9514 -> 10757 bytes .../figure-html/benchmark_SFO_SFO-1.png | Bin 11028 -> 10610 bytes docs/articles/mkin.html | 2 +- docs/articles/mkin_cache/html/__packages | 2 - ...-chunk-2_1255937aa4f0d68ff78163262b20b976.RData | Bin 0 -> 3367 bytes ...ed-chunk-2_1255937aa4f0d68ff78163262b20b976.rdb | Bin 0 -> 20287 bytes ...ed-chunk-2_1255937aa4f0d68ff78163262b20b976.rdx | Bin 0 -> 225 bytes .../mkin_files/figure-html/unnamed-chunk-2-1.png | Bin 112161 -> 45379 bytes docs/index.html | 6 +- docs/reference/Extract.mmkin.html | 24 +- docs/reference/SFO.solution-2.png | Bin 0 -> 6424 bytes docs/reference/SFO.solution.html | 2 +- docs/reference/SFORB.solution-2.png | Bin 0 -> 6788 bytes docs/reference/SFORB.solution.html | 2 +- docs/reference/index.html | 91 +- docs/reference/mccall81_245T.html | 250 ++- docs/reference/mkinfit.html | 2169 +++++++++++++++++++- docs/reference/mkinmod.html | 62 +- docs/reference/mkinpredict.html | 6 +- docs/reference/mmkin-14.png | Bin 0 -> 30013 bytes docs/reference/mmkin-16.png | Bin 0 -> 27062 bytes docs/reference/mmkin-18.png | Bin 0 -> 25359 bytes docs/reference/mmkin-20.png | Bin 0 -> 18905 bytes docs/reference/mmkin-22.png | Bin 0 -> 17036 bytes docs/reference/mmkin.html | 1129 +++++++++- docs/reference/schaefer07_complex_case.html | 1054 +++++++++- docs/reference/summary.mkinfit.html | 6 +- docs/reference/synthetic_data_for_UBA.html | 872 +++++++- docs/reference/transform_odeparms.html | 527 ++++- man/mkinfit.Rd | 4 +- man/schaefer07_complex_case.Rd | 2 +- 45 files changed, 6005 insertions(+), 289 deletions(-) create mode 100644 docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.RData create mode 100644 docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdb create mode 100644 docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdx create mode 100644 docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.RData create mode 100644 docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdb create mode 100644 docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdx create mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_1255937aa4f0d68ff78163262b20b976.RData create mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_1255937aa4f0d68ff78163262b20b976.rdb create mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_1255937aa4f0d68ff78163262b20b976.rdx create mode 100644 docs/reference/SFO.solution-2.png create mode 100644 docs/reference/SFORB.solution-2.png create mode 100644 docs/reference/mmkin-14.png create mode 100644 docs/reference/mmkin-16.png create mode 100644 docs/reference/mmkin-18.png create mode 100644 docs/reference/mmkin-20.png create mode 100644 docs/reference/mmkin-22.png diff --git a/GNUmakefile b/GNUmakefile index fd9e72b8..7d58995b 100644 --- a/GNUmakefile +++ b/GNUmakefile @@ -87,9 +87,9 @@ vignettes/%.html: vignettes/mkin_vignettes.css vignettes/%.Rmd vignettes: vignettes/mkin.html vignettes/FOCUS_D.html vignettes/FOCUS_L.html vignettes/FOCUS_Z.pdf vignettes/compiled_models.html pd: - "$(RBIN)/Rscript" -e "pkgdown::build_site()" + "$(RBIN)/Rscript" -e "pkgdown::build_site(run_dont_run = TRUE)" git add -A - git commit -m 'Static documentation rebuilt by pkgdown::build_site()' -e + git commit -m 'Static documentation rebuilt by pkgdown::build_site(run_dont_run = TRUE)' -e r-forge: pd rm -rf $(SDDIR)/* diff --git a/_pkgdown.yml b/_pkgdown.yml index a46bc34f..70fdcaa9 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -26,7 +26,7 @@ reference: - plot.mmkin - title: Datasets and known results contents: - - FOCUS_2006_datasets + - FOCUS_2006_A - FOCUS_2006_SFO_ref_A_to_F - FOCUS_2006_FOMC_ref_A_to_F - FOCUS_2006_HS_ref_A_to_F @@ -41,7 +41,6 @@ reference: - mkin_wide_to_long - mkin_long_to_wide - mkinsub - - mkinds, print.mkinds - print.mkinmod - mkinpredict - transform_odeparms @@ -50,6 +49,7 @@ reference: - title: Analytical solutions desc: Parent only model solutions contents: + - ends_with(".solution") - SFO.solution - FOMC.solution - DFOP.solution diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index 776e1093..0ce7bd07 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -41,7 +41,7 @@

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

-

2016-11-17

+

2016-11-18

diff --git a/docs/articles/FOCUS_D_cache/html/__packages b/docs/articles/FOCUS_D_cache/html/__packages index f8bbf624..c3c384b1 100644 --- a/docs/articles/FOCUS_D_cache/html/__packages +++ b/docs/articles/FOCUS_D_cache/html/__packages @@ -8,5 +8,3 @@ inline mkin rmarkdown knitr -microbenchmark -ggplot2 diff --git a/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.RData b/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.RData new file mode 100644 index 00000000..36a4095f Binary files /dev/null and b/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.RData differ diff --git a/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdb b/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdb new file mode 100644 index 00000000..e69de29b diff --git a/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdx b/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdx new file mode 100644 index 00000000..20f10d9f Binary files /dev/null and b/docs/articles/FOCUS_D_cache/html/plot_2_a17fdb1fd55c48e44fecf3303fab9127.rdx differ diff --git a/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.RData b/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.RData new file mode 100644 index 00000000..b0731d7b Binary files /dev/null and b/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.RData differ diff --git a/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdb b/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdb new file mode 100644 index 00000000..e69de29b diff --git a/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdx b/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdx new file mode 100644 index 00000000..20f10d9f Binary files /dev/null and b/docs/articles/FOCUS_D_cache/html/plot_7ea6a8e7d5684cd6a8daf57a478ef419.rdx differ diff --git a/docs/articles/FOCUS_D_files/figure-html/plot-1.png b/docs/articles/FOCUS_D_files/figure-html/plot-1.png index fc237898..e44c1374 100644 Binary files a/docs/articles/FOCUS_D_files/figure-html/plot-1.png and b/docs/articles/FOCUS_D_files/figure-html/plot-1.png differ diff --git a/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png b/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png index b0a7c26b..c7df3486 100644 Binary files a/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png and b/docs/articles/FOCUS_D_files/figure-html/plot_2-1.png differ diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html index e7ec5308..c3009e4d 100644 --- a/docs/articles/FOCUS_L.html +++ b/docs/articles/FOCUS_L.html @@ -41,7 +41,7 @@

Example evaluation of FOCUS Laboratory Data L1 to L3

Johannes Ranke

-

2016-11-17

+

2016-11-18

@@ -63,15 +63,15 @@ FOCUS_2006_L1_mkin <- summary(m.L1.SFO) 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:18 2016 
-## Date of summary: Thu Nov 17 22:58:18 2016 
+## Date of fit:     Fri Nov 18 15:22:03 2016 
+## Date of summary: Fri Nov 18 15:22:03 2016 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.103 s
+## Fitted with method Port using 37 model solutions performed in 0.09 s
 ## 
 ## Weighting: none
 ## 
@@ -156,8 +156,8 @@ FOCUS_2006_L1_mkin <- 
summary(m.L1.FOMC, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:19 2016 
-## Date of summary: Thu Nov 17 22:58:19 2016 
+## Date of fit:     Fri Nov 18 15:22:04 2016 
+## Date of summary: Fri Nov 18 15:22:04 2016 
 ## 
 ## 
 ## Warning: Optimisation by method Port did not converge.
@@ -169,7 +169,7 @@ FOCUS_2006_L1_mkin <-  
summary(m.L2.FOMC, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:20 2016 
-## Date of summary: Thu Nov 17 22:58:20 2016 
+## Date of fit:     Fri Nov 18 15:22:05 2016 
+## Date of summary: Fri Nov 18 15:22:05 2016 
 ## 
 ## 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 0.19 s
 ## 
 ## Weighting: none
 ## 
@@ -323,8 +323,8 @@ FOCUS_2006_L2_mkin <- 
summary(m.L2.DFOP, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:21 2016 
-## Date of summary: Thu Nov 17 22:58:21 2016 
+## Date of fit:     Fri Nov 18 15:22:06 2016 
+## Date of summary: Fri Nov 18 15:22:06 2016 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -333,7 +333,7 @@ FOCUS_2006_L2_mkin <-  
summary(mm.L3[["DFOP", 1]])

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:22 2016 
-## Date of summary: Thu Nov 17 22:58:22 2016 
+## Date of fit:     Fri Nov 18 15:22:07 2016 
+## Date of summary: Fri Nov 18 15:22:07 2016 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -422,7 +422,7 @@ mm.L3 <-  
summary(mm.L4[["SFO", 1]], data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:22 2016 
-## Date of summary: Thu Nov 17 22:58:23 2016 
+## Date of fit:     Fri Nov 18 15:22:08 2016 
+## Date of summary: Fri Nov 18 15:22:08 2016 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.114 s
+## Fitted with method Port using 46 model solutions performed in 0.109 s
 ## 
 ## Weighting: none
 ## 
@@ -572,15 +572,15 @@ mm.L4 <- 
summary(mm.L4[["FOMC", 1]], data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Thu Nov 17 22:58:23 2016 
-## Date of summary: Thu Nov 17 22:58:23 2016 
+## Date of fit:     Fri Nov 18 15:22:08 2016 
+## Date of summary: Fri Nov 18 15:22:08 2016 
 ## 
 ## 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 0.151 s
+## Fitted with method Port using 66 model solutions performed in 0.15 s
 ## 
 ## Weighting: none
 ## 
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 1446a357..ce149bc5 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -41,7 +41,7 @@
       
Performance benefit by using compiled model definitions in mkin

                         
Johannes Ranke

             
-            
2016-11-17

+            
2016-11-18

           
 
     
@@ -78,21 +78,21 @@ mb.1 <- micr
 print(mb.1)

 
## Unit: milliseconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 6251.2433 6291.2435 6315.5160 6331.2438 6347.6524
-##       Eigenvalue based  858.2035  903.1770  926.2132  948.1505  960.2181
-##      deSolve, compiled  721.0067  739.1361  745.9964  757.2656  758.4913
+##  deSolve, not compiled 6341.1795 6363.5977 6373.7748 6386.0158 6390.0724
+##       Eigenvalue based  907.1699  908.8498  921.8335  910.5297  929.1653
+##      deSolve, compiled  747.5311  752.3718  754.2086  757.2125  757.5474
 ##        max neval cld
-##  6364.0611     3   c
-##   972.2856     3  b 
-##   759.7171     3 a

+##  6394.1290     3   c
+##   947.8008     3  b 
+##   757.8823     3 a

 
autoplot(mb.1)

 

 
We see that using the compiled model is by a factor of 8.4 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs:

 
rownames(smb.1) <- smb.1$expr
 smb.1["median"]/smb.1["deSolve, compiled", "median"]

 
##                         median
-## deSolve, not compiled 8.360665
-## Eigenvalue based      1.252071
+## deSolve, not compiled 8.433585
+## Eigenvalue based      1.202476
 ## deSolve, compiled     1.000000

 
 

@@ -114,11 +114,11 @@ smb.1["median"]/smbprint(mb.2)

 
## Unit: seconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 13.601046 13.602861 13.619563 13.604676 13.628821
-##      deSolve, compiled  1.341581  1.346263  1.348298  1.350944  1.351657
-##       max neval cld
-##  13.65297     3   b
-##   1.35237     3  a

+##  deSolve, not compiled 13.214250 13.248908 13.384577 13.283565 13.469740
+##      deSolve, compiled  1.303868  1.307484  1.332879  1.311099  1.347384
+##        max neval cld
+##  13.655915     3   b
+##   1.383669     3  a

 
smb.2["median"]/smb.2["deSolve, compiled", "median"]

 
##   median
 ## 1     NA
diff --git a/docs/articles/compiled_models_files/figure-html/benchmark_FOMC_SFO-1.png b/docs/articles/compiled_models_files/figure-html/benchmark_FOMC_SFO-1.png
index 3c3b9c54..53b631b1 100644
Binary files a/docs/articles/compiled_models_files/figure-html/benchmark_FOMC_SFO-1.png and b/docs/articles/compiled_models_files/figure-html/benchmark_FOMC_SFO-1.png differ
diff --git a/docs/articles/compiled_models_files/figure-html/benchmark_SFO_SFO-1.png b/docs/articles/compiled_models_files/figure-html/benchmark_SFO_SFO-1.png
index 0ec027f1..6d78194f 100644
Binary files a/docs/articles/compiled_models_files/figure-html/benchmark_SFO_SFO-1.png and b/docs/articles/compiled_models_files/figure-html/benchmark_SFO_SFO-1.png differ
diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html
index 4eed053a..8134287b 100644
--- a/docs/articles/mkin.html
+++ b/docs/articles/mkin.html
@@ -41,7 +41,7 @@
       
mkin - Kinetic evaluation of chemical degradation data

                         
Johannes Ranke

             
-            
2016-11-17

+            
2016-11-18

           
 
     
diff --git a/docs/articles/mkin_cache/html/__packages b/docs/articles/mkin_cache/html/__packages
index ff62e6df..ae46e2d7 100644
--- a/docs/articles/mkin_cache/html/__packages
+++ b/docs/articles/mkin_cache/html/__packages
@@ -8,5 +8,3 @@ colorout
 setwidth
 nvimcom
 rmarkdown
-microbenchmark
-ggplot2
diff --git a/docs/articles/mkin_cache/html/unnamed-chunk-2_1255937aa4f0d68ff78163262b20b976.RData b/docs/articles/mkin_cache/html/unnamed-chunk-2_1255937aa4f0d68ff78163262b20b976.RData
new file mode 100644
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new file mode 100644
index 00000000..2b71e52b
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diff --git a/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png b/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png
index d34e3805..2e7e2244 100644
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diff --git a/docs/index.html b/docs/index.html
index 444b650e..93be361e 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -85,16 +85,16 @@
 

 

  News

-
Yes, there is a ChangeLog, for the latest CRAN release and one for the github master branch.

+
Yes, there is a ChangeLog, for the latest CRAN release and one for the github master branch.

 

 

 

  Credits and historical remarks

-
mkin would not be possible without the underlying software stack consisting of R and the packages deSolve and FME, to say the least.

+
mkin would not be possible without the underlying software stack consisting of R and the packages deSolve and FME, to say the least.

 
It could not have been written without me being introduced to regulatory fate modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories Ltd (formerly RCC Ltd). mkin greatly profits from and largely follows the work done by the FOCUS Degradation Kinetics Workgroup, as detailed in their guidance document from 2006, slightly updated in 2011 and in 2014.

 
Also, it was inspired by the first version of KinGUI developed by BayerCropScience, which is based on the MatLab runtime environment.

 
The companion package kinfit (now deprecated) was started in 2008 and first published on CRAN on 01 May 2010.

-
The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.

+
The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.

 
In 2011, Bayer Crop Science started to distribute an R based successor to KinGUI named KinGUII whose R code is based on mkin, but which added, amongst other refinements, a closed source graphical user interface (GUI), iteratively reweighted least squares (IRLS) optimisation of the variance for each of the observed variables, and Markov Chain Monte Carlo (MCMC) simulation functionality, similar to what is available e.g. in the FME package.

 
Somewhat in parallel, Syngenta has sponsored the development of an mkin and KinGUII based GUI application called CAKE, which also adds IRLS and MCMC, is more limited in the model formulation, but puts more weight on usability. CAKE is available for download from the CAKE website, where you can also find a zip archive of the R scripts derived from mkin, published under the GPL license.

 
Finally, there is KineticEval, which contains a further development of the scripts used for KinGUII, so the different tools will hopefully be able to learn from each other in the future as well.

diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html
index b437fc7d..09d7513c 100644
--- a/docs/reference/Extract.mmkin.html
+++ b/docs/reference/Extract.mmkin.html
@@ -193,7 +193,7 @@
 #> 
 #> $time
 #>    user  system elapsed 
-#>   0.268   0.000   0.267 
+#>   0.256   0.000   0.255 
 #> 
 #> $mkinmod
 #> <mkinmod> model generated with
@@ -379,7 +379,7 @@
 #>     }
 #>     return(mC)
 #> }
-#> <environment: 0x3a2f9e8>
+#> <environment: 0x3fc5fa0>
 #> 
 #> $cost_notrans
 #> function (P) 
@@ -401,7 +401,7 @@
 #>         scaleVar = scaleVar)
 #>     return(mC)
 #> }
-#> <environment: 0x3a2f9e8>
+#> <environment: 0x3fc5fa0>
 #> 
 #> $hessian_notrans
 #>            parent_0     alpha       beta
@@ -467,7 +467,7 @@
 #> 99.66619 
 #> 
 #> $date
-#> [1] "Thu Nov 17 22:56:49 2016"
+#> [1] "Fri Nov 18 15:19:25 2016"
 #> 
 #> attr(,"class")
 #> [1] "mkinfit" "modFit" 
  fits["SFO", "B"]
#>      dataset
@@ -546,7 +546,7 @@
 #> 
 #> $time
 #>    user  system elapsed 
-#>   0.116   0.000   0.115 
+#>   0.064   0.000   0.066 
 #> 
 #> $mkinmod
 #> <mkinmod> model generated with
@@ -733,7 +733,7 @@
 #>     }
 #>     return(mC)
 #> }
-#> <environment: 0x42fb560>
+#> <environment: 0x3b66828>
 #> 
 #> $cost_notrans
 #> function (P) 
@@ -755,7 +755,7 @@
 #>         scaleVar = scaleVar)
 #>     return(mC)
 #> }
-#> <environment: 0x42fb560>
+#> <environment: 0x3b66828>
 #> 
 #> $hessian_notrans
 #>                   parent_0 k_parent_sink
@@ -818,7 +818,7 @@
 #> 99.17407 
 #> 
 #> $date
-#> [1] "Thu Nov 17 22:56:48 2016"
+#> [1] "Fri Nov 18 15:19:25 2016"
 #> 
 #> attr(,"class")
 #> [1] "mkinfit" "modFit" 
  fits["SFO", "B", drop = TRUE]
#> [[1]]
@@ -894,7 +894,7 @@
 #> 
 #> $time
 #>    user  system elapsed 
-#>   0.116   0.000   0.115 
+#>   0.064   0.000   0.066 
 #> 
 #> $mkinmod
 #> <mkinmod> model generated with
@@ -1081,7 +1081,7 @@
 #>     }
 #>     return(mC)
 #> }
-#> <environment: 0x42fb560>
+#> <environment: 0x3b66828>
 #> 
 #> $cost_notrans
 #> function (P) 
@@ -1103,7 +1103,7 @@
 #>         scaleVar = scaleVar)
 #>     return(mC)
 #> }
-#> <environment: 0x42fb560>
+#> <environment: 0x3b66828>
 #> 
 #> $hessian_notrans
 #>                   parent_0 k_parent_sink
@@ -1166,7 +1166,7 @@
 #> 99.17407 
 #> 
 #> $date
-#> [1] "Thu Nov 17 22:56:48 2016"
+#> [1] "Fri Nov 18 15:19:25 2016"
 #> 
 #> attr(,"class")
 #> [1] "mkinfit" "modFit" 
diff --git a/docs/reference/SFO.solution-2.png b/docs/reference/SFO.solution-2.png
new file mode 100644
index 00000000..78c083c3
Binary files /dev/null and b/docs/reference/SFO.solution-2.png differ
diff --git a/docs/reference/SFO.solution.html b/docs/reference/SFO.solution.html
index 2ead8f24..30d7acdf 100644
--- a/docs/reference/SFO.solution.html
+++ b/docs/reference/SFO.solution.html
@@ -110,7 +110,7 @@
     
 
     
Examples

-    
  ## Not run: plot(function(x) SFO.solution(x, 100, 3), 0, 2)

+    
  plot(function(x) SFO.solution(x, 100, 3), 0, 2)

   

   
   
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D)
#> Model cost at call  1 :  18857.28 
+#> Model cost at call  4 :  18857.28 
+#> Model cost at call  5 :  18857.28 
+#> Model cost at call  8 :  15273.94 
+#> Model cost at call  9 :  15273.93 
+#> Model cost at call  12 :  15273.67 
+#> Model cost at call  13 :  15273.64 
+#> Model cost at call  14 :  12764.42 
+#> Model cost at call  15 :  8382.7 
+#> Model cost at call  20 :  8382.696 
+#> Model cost at call  23 :  2729.177 
+#> Model cost at call  24 :  2729.175 
+#> Model cost at call  26 :  2729.164 
+#> Model cost at call  30 :  2299.383 
+#> Model cost at call  34 :  2299.379 
+#> Model cost at call  35 :  2299.373 
+#> Model cost at call  36 :  1944.782 
+#> Model cost at call  40 :  1944.782 
+#> Model cost at call  42 :  1328.087 
+#> Model cost at call  43 :  908.661 
+#> Model cost at call  44 :  908.6604 
+#> Model cost at call  50 :  877.3556 
+#> Model cost at call  51 :  877.3554 
+#> Model cost at call  54 :  877.3546 
+#> Model cost at call  56 :  769.5186 
+#> Model cost at call  59 :  769.5157 
+#> Model cost at call  62 :  690.3426 
+#> Model cost at call  66 :  690.3425 
+#> Model cost at call  68 :  608.4032 
+#> Model cost at call  72 :  608.4031 
+#> Model cost at call  73 :  608.4031 
+#> Model cost at call  74 :  601.5178 
+#> Model cost at call  78 :  601.5174 
+#> Model cost at call  79 :  601.5174 
+#> Model cost at call  80 :  459.9885 
+#> Model cost at call  81 :  459.9883 
+#> Model cost at call  83 :  459.9878 
+#> Model cost at call  87 :  447.0145 
+#> Model cost at call  91 :  447.0145 
+#> Model cost at call  94 :  445.7322 
+#> Model cost at call  97 :  445.7322 
+#> Model cost at call  99 :  445.7322 
+#> Model cost at call  100 :  444.6965 
+#> Model cost at call  103 :  444.6965 
+#> Model cost at call  106 :  442.9742 
+#> Model cost at call  109 :  442.9742 
+#> Model cost at call  112 :  439.9665 
+#> Model cost at call  115 :  439.9665 
+#> Model cost at call  116 :  439.9664 
+#> Model cost at call  118 :  435.0752 
+#> Model cost at call  121 :  435.0751 
+#> Model cost at call  124 :  430.4718 
+#> Model cost at call  127 :  430.4717 
+#> Model cost at call  132 :  424.7004 
+#> Model cost at call  134 :  424.7003 
+#> Model cost at call  138 :  423.6102 
+#> Model cost at call  141 :  423.6102 
+#> Model cost at call  142 :  423.6102 
+#> Model cost at call  144 :  421.1786 
+#> Model cost at call  147 :  421.1786 
+#> Model cost at call  148 :  421.1786 
+#> Model cost at call  150 :  418.1431 
+#> Model cost at call  151 :  412.8665 
+#> Model cost at call  152 :  396.6067 
+#> Model cost at call  154 :  396.6067 
+#> Model cost at call  158 :  391.0492 
+#> Model cost at call  160 :  391.0492 
+#> Model cost at call  164 :  385.8205 
+#> Model cost at call  165 :  385.8205 
+#> Model cost at call  170 :  379.7674 
+#> Model cost at call  171 :  379.7674 
+#> Model cost at call  172 :  379.7674 
+#> Model cost at call  176 :  374.9389 
+#> Model cost at call  177 :  374.9389 
+#> Model cost at call  182 :  372.727 
+#> Model cost at call  185 :  372.727 
+#> Model cost at call  188 :  371.5297 
+#> Model cost at call  194 :  370.3738 
+#> Model cost at call  195 :  370.3738 
+#> Model cost at call  200 :  370.0182 
+#> Model cost at call  206 :  369.8634 
+#> Model cost at call  212 :  369.8188 
+#> Model cost at call  213 :  369.8188 
+#> Model cost at call  219 :  369.8114 
+#> Model cost at call  221 :  369.8114 
+#> Model cost at call  224 :  369.8114 
+#> Model cost at call  226 :  369.8114 
+#> Model cost at call  230 :  369.8105 
+#> Model cost at call  231 :  369.8105 
+#> Model cost at call  235 :  369.8105 
+#> Model cost at call  236 :  369.8105 
+#> Model cost at call  237 :  369.8105 
+#> Model cost at call  238 :  369.8105 
+#> Model cost at call  249 :  369.8105 
+#> Model cost at call  260 :  369.8105 
+#> Model cost at call  275 :  369.8105 
+#> Model cost at call  276 :  369.8105 
+#> Optimisation by method Port successfully terminated.
# Use starting parameters from parent only FOMC fit
+fit.FOMC = mkinfit("FOMC", FOCUS_2006_D)
#> Model cost at call  1 :  3237.008 
+#> Model cost at call  3 :  3237.007 
+#> Model cost at call  6 :  671.2571 
+#> Model cost at call  7 :  671.2559 
+#> Model cost at call  8 :  671.2301 
+#> Model cost at call  9 :  671.2249 
+#> Model cost at call  10 :  468.4899 
+#> Model cost at call  12 :  468.4899 
+#> Model cost at call  14 :  371.3486 
+#> Model cost at call  16 :  371.3485 
+#> Model cost at call  18 :  346.2972 
+#> Model cost at call  19 :  346.2971 
+#> Model cost at call  20 :  346.297 
+#> Model cost at call  21 :  346.2969 
+#> Model cost at call  22 :  269.7053 
+#> Model cost at call  23 :  269.7053 
+#> Model cost at call  26 :  243.9936 
+#> Model cost at call  27 :  235.1625 
+#> Model cost at call  28 :  235.1624 
+#> Model cost at call  30 :  235.1624 
+#> Model cost at call  31 :  224.2195 
+#> Model cost at call  35 :  218.1922 
+#> Model cost at call  36 :  218.1922 
+#> Model cost at call  38 :  218.1922 
+#> Model cost at call  39 :  211.5012 
+#> Model cost at call  41 :  211.5012 
+#> Model cost at call  43 :  207.9511 
+#> Model cost at call  44 :  207.9511 
+#> Model cost at call  47 :  206.5377 
+#> Model cost at call  51 :  205.8736 
+#> Model cost at call  55 :  205.5625 
+#> Model cost at call  59 :  205.4704 
+#> Model cost at call  63 :  205.4499 
+#> Model cost at call  67 :  205.448 
+#> Model cost at call  69 :  205.448 
+#> Model cost at call  70 :  205.448 
+#> Model cost at call  73 :  205.448 
+#> Model cost at call  74 :  205.4478 
+#> Model cost at call  75 :  205.4478 
+#> Model cost at call  77 :  205.4478 
+#> Model cost at call  79 :  205.4478 
+#> Model cost at call  84 :  205.4478 
+#> Model cost at call  95 :  205.4478 
+#> Model cost at call  98 :  205.4478 
+#> Optimisation by method Port successfully terminated.
fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D,
+  parms.ini = fit.FOMC$bparms.ode)
#> Model cost at call  1 :  15169.96 
+#> Model cost at call  2 :  15169.96 
+#> Model cost at call  7 :  8247.462 
+#> Model cost at call  14 :  6734.371 
+#> Model cost at call  15 :  6734.339 
+#> Model cost at call  16 :  6734.136 
+#> Model cost at call  20 :  4855.056 
+#> Model cost at call  24 :  4855.038 
+#> Model cost at call  27 :  1239.986 
+#> Model cost at call  29 :  1239.985 
+#> Model cost at call  34 :  1030.523 
+#> Model cost at call  38 :  1030.523 
+#> Model cost at call  40 :  894.2766 
+#> Model cost at call  43 :  894.275 
+#> Model cost at call  46 :  750.3629 
+#> Model cost at call  49 :  750.3623 
+#> Model cost at call  52 :  627.6819 
+#> Model cost at call  55 :  627.6818 
+#> Model cost at call  58 :  546.2947 
+#> Model cost at call  61 :  546.2944 
+#> Model cost at call  65 :  502.5529 
+#> Model cost at call  69 :  502.5525 
+#> Model cost at call  70 :  502.5525 
+#> Model cost at call  71 :  475.2423 
+#> Model cost at call  72 :  465.5298 
+#> Model cost at call  75 :  465.5298 
+#> Model cost at call  76 :  465.5297 
+#> Model cost at call  78 :  464.9476 
+#> Model cost at call  81 :  464.9476 
+#> Model cost at call  82 :  464.9473 
+#> Model cost at call  84 :  426.9626 
+#> Model cost at call  88 :  426.9626 
+#> Model cost at call  90 :  414.5235 
+#> Model cost at call  93 :  414.5234 
+#> Model cost at call  96 :  412.1478 
+#> Model cost at call  99 :  412.1477 
+#> Model cost at call  100 :  412.1477 
+#> Model cost at call  101 :  412.1477 
+#> Model cost at call  102 :  394.146 
+#> Model cost at call  105 :  394.146 
+#> Model cost at call  106 :  394.146 
+#> Model cost at call  107 :  394.146 
+#> Model cost at call  108 :  384.2002 
+#> Model cost at call  112 :  384.2001 
+#> Model cost at call  113 :  384.2001 
+#> Model cost at call  115 :  380.5495 
+#> Model cost at call  119 :  380.5494 
+#> Model cost at call  120 :  380.5494 
+#> Model cost at call  121 :  378.4803 
+#> Model cost at call  123 :  378.4802 
+#> Model cost at call  124 :  378.4792 
+#> Model cost at call  127 :  374.8432 
+#> Model cost at call  129 :  374.8431 
+#> Model cost at call  133 :  372.8364 
+#> Model cost at call  136 :  372.8364 
+#> Model cost at call  137 :  372.8363 
+#> Model cost at call  138 :  372.8363 
+#> Model cost at call  141 :  372.668 
+#> Model cost at call  145 :  372.6679 
+#> Model cost at call  147 :  372.5882 
+#> Model cost at call  150 :  372.5882 
+#> Model cost at call  153 :  372.4828 
+#> Model cost at call  156 :  372.4828 
+#> Model cost at call  159 :  372.3639 
+#> Model cost at call  162 :  372.3639 
+#> Model cost at call  163 :  372.3639 
+#> Model cost at call  164 :  372.3639 
+#> Model cost at call  165 :  372.1959 
+#> Model cost at call  168 :  372.1959 
+#> Model cost at call  171 :  371.9627 
+#> Model cost at call  172 :  371.7467 
+#> Model cost at call  173 :  371.1161 
+#> Model cost at call  174 :  370.3326 
+#> Model cost at call  177 :  370.3326 
+#> Model cost at call  178 :  370.3326 
+#> Model cost at call  180 :  370.3267 
+#> Model cost at call  186 :  370.0471 
+#> Model cost at call  187 :  370.0471 
+#> Model cost at call  193 :  369.9649 
+#> Model cost at call  194 :  369.9649 
+#> Model cost at call  196 :  369.9649 
+#> Model cost at call  199 :  369.8684 
+#> Model cost at call  200 :  369.8684 
+#> Model cost at call  204 :  369.8684 
+#> Model cost at call  206 :  369.8349 
+#> Model cost at call  207 :  369.8349 
+#> Model cost at call  209 :  369.8349 
+#> Model cost at call  210 :  369.8349 
+#> Model cost at call  211 :  369.8349 
+#> Model cost at call  212 :  369.8105 
+#> Model cost at call  214 :  369.8105 
+#> Model cost at call  218 :  369.8105 
+#> Model cost at call  220 :  369.8105 
+#> Model cost at call  225 :  369.8105 
+#> Model cost at call  229 :  369.8105 
+#> Model cost at call  231 :  369.8105 
+#> Model cost at call  232 :  369.8105 
+#> Model cost at call  236 :  369.8105 
+#> Model cost at call  239 :  369.8105 
+#> Model cost at call  240 :  369.8105 
+#> Model cost at call  255 :  369.8105 
+#> Model cost at call  258 :  369.8105 
+#> Optimisation by method Port successfully terminated.

+# 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"))
#> Successfully compiled differential equation model from auto-generated C code.
# Fit the model to the FOCUS example dataset D using defaults
+fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D)
#> Model cost at call  1 :  19233.21 
+#> Model cost at call  2 :  19233.21 
+#> Model cost at call  5 :  19233.21 
+#> Model cost at call  8 :  14482.65 
+#> Model cost at call  11 :  14482.51 
+#> Model cost at call  13 :  14482.17 
+#> Model cost at call  15 :  6973.814 
+#> Model cost at call  16 :  5161.041 
+#> Model cost at call  17 :  5161.029 
+#> Model cost at call  22 :  5161.026 
+#> Model cost at call  24 :  3249.595 
+#> Model cost at call  26 :  3249.595 
+#> Model cost at call  27 :  3249.519 
+#> Model cost at call  31 :  2615.891 
+#> Model cost at call  32 :  2615.888 
+#> Model cost at call  39 :  989.1788 
+#> Model cost at call  44 :  989.1772 
+#> Model cost at call  45 :  989.1771 
+#> Model cost at call  47 :  647.4307 
+#> Model cost at call  50 :  647.4302 
+#> Model cost at call  51 :  647.4261 
+#> Model cost at call  54 :  626.7937 
+#> Model cost at call  55 :  626.7935 
+#> Model cost at call  56 :  626.7931 
+#> Model cost at call  61 :  527.9042 
+#> Model cost at call  62 :  527.9041 
+#> Model cost at call  68 :  505.8828 
+#> Model cost at call  70 :  505.8828 
+#> Model cost at call  73 :  505.8827 
+#> Model cost at call  75 :  452.8932 
+#> Model cost at call  77 :  452.893 
+#> Model cost at call  82 :  414.4918 
+#> Model cost at call  83 :  414.4918 
+#> Model cost at call  84 :  414.4918 
+#> Model cost at call  88 :  414.4917 
+#> Model cost at call  89 :  408.2617 
+#> Model cost at call  90 :  408.2616 
+#> Model cost at call  91 :  408.2616 
+#> Model cost at call  95 :  408.2615 
+#> Model cost at call  96 :  384.4461 
+#> Model cost at call  102 :  384.4461 
+#> Model cost at call  104 :  383.4905 
+#> Model cost at call  105 :  383.4905 
+#> Model cost at call  106 :  383.4905 
+#> Model cost at call  109 :  383.4904 
+#> Model cost at call  111 :  381.8828 
+#> Model cost at call  112 :  381.8827 
+#> Model cost at call  118 :  380.8499 
+#> Model cost at call  120 :  380.8499 
+#> Model cost at call  123 :  380.8499 
+#> Model cost at call  125 :  379.1403 
+#> Model cost at call  127 :  379.1402 
+#> Model cost at call  132 :  376.4962 
+#> Model cost at call  133 :  373.0958 
+#> Model cost at call  134 :  365.247 
+#> Model cost at call  137 :  365.2469 
+#> Model cost at call  142 :  360.8231 
+#> Model cost at call  143 :  360.8231 
+#> Model cost at call  146 :  360.8231 
+#> Model cost at call  148 :  360.8231 
+#> Model cost at call  149 :  358.3976 
+#> Model cost at call  152 :  358.3976 
+#> Model cost at call  154 :  358.3976 
+#> Model cost at call  156 :  355.9066 
+#> Model cost at call  157 :  355.9066 
+#> Model cost at call  163 :  354.3386 
+#> Model cost at call  164 :  353.6335 
+#> Model cost at call  172 :  353.2094 
+#> Model cost at call  173 :  353.2094 
+#> Model cost at call  174 :  353.2093 
+#> Model cost at call  177 :  353.2093 
+#> Model cost at call  178 :  353.2093 
+#> Model cost at call  179 :  352.6641 
+#> Model cost at call  182 :  352.6641 
+#> Model cost at call  183 :  352.6641 
+#> Model cost at call  186 :  352.4908 
+#> Model cost at call  187 :  352.4429 
+#> Model cost at call  195 :  352.3246 
+#> Model cost at call  203 :  352.2858 
+#> Model cost at call  204 :  352.2858 
+#> Model cost at call  205 :  352.2858 
+#> Model cost at call  206 :  352.2858 
+#> Model cost at call  207 :  352.2858 
+#> Model cost at call  210 :  352.2332 
+#> Model cost at call  211 :  352.2081 
+#> Model cost at call  214 :  352.2081 
+#> Model cost at call  216 :  352.2081 
+#> Model cost at call  218 :  352.2049 
+#> Model cost at call  219 :  352.2049 
+#> Model cost at call  220 :  352.2049 
+#> Model cost at call  226 :  352.2048 
+#> Model cost at call  228 :  352.2048 
+#> Model cost at call  231 :  352.2048 
+#> Model cost at call  232 :  352.2048 
+#> Model cost at call  238 :  352.2048 
+#> Model cost at call  239 :  352.2048 
+#> Model cost at call  251 :  352.2048 
+#> Model cost at call  264 :  352.2048 
+#> Model cost at call  283 :  352.2048 
+#> Model cost at call  284 :  352.2048 
+#> Model cost at call  285 :  352.2048 
+#> Model cost at call  286 :  352.2048 
+#> Optimisation by method Port successfully terminated.
fit.SFORB_SFO.deSolve <- mkinfit(SFORB_SFO, FOCUS_2006_D, solution_type = "deSolve")
#> Model cost at call  1 :  19233.21 
+#> Model cost at call  2 :  19233.21 
+#> Model cost at call  5 :  19233.21 
+#> Model cost at call  8 :  14482.65 
+#> Model cost at call  11 :  14482.51 
+#> Model cost at call  13 :  14482.17 
+#> Model cost at call  15 :  6973.814 
+#> Model cost at call  16 :  5161.041 
+#> Model cost at call  17 :  5161.029 
+#> Model cost at call  22 :  5161.026 
+#> Model cost at call  24 :  3249.595 
+#> Model cost at call  26 :  3249.595 
+#> Model cost at call  27 :  3249.519 
+#> Model cost at call  31 :  2615.891 
+#> Model cost at call  32 :  2615.888 
+#> Model cost at call  39 :  989.1788 
+#> Model cost at call  44 :  989.1772 
+#> Model cost at call  45 :  989.1771 
+#> Model cost at call  47 :  647.4307 
+#> Model cost at call  50 :  647.4302 
+#> Model cost at call  51 :  647.4261 
+#> Model cost at call  54 :  626.7937 
+#> Model cost at call  55 :  626.7935 
+#> Model cost at call  56 :  626.7931 
+#> Model cost at call  61 :  527.9042 
+#> Model cost at call  62 :  527.9041 
+#> Model cost at call  68 :  505.8828 
+#> Model cost at call  70 :  505.8828 
+#> Model cost at call  73 :  505.8827 
+#> Model cost at call  75 :  452.8932 
+#> Model cost at call  77 :  452.893 
+#> Model cost at call  82 :  414.4918 
+#> Model cost at call  83 :  414.4918 
+#> Model cost at call  84 :  414.4918 
+#> Model cost at call  88 :  414.4917 
+#> Model cost at call  89 :  408.2617 
+#> Model cost at call  90 :  408.2616 
+#> Model cost at call  91 :  408.2616 
+#> Model cost at call  95 :  408.2615 
+#> Model cost at call  96 :  384.4461 
+#> Model cost at call  102 :  384.4461 
+#> Model cost at call  104 :  383.4905 
+#> Model cost at call  105 :  383.4905 
+#> Model cost at call  106 :  383.4905 
+#> Model cost at call  109 :  383.4904 
+#> Model cost at call  111 :  381.8828 
+#> Model cost at call  112 :  381.8827 
+#> Model cost at call  118 :  380.8499 
+#> Model cost at call  120 :  380.8499 
+#> Model cost at call  123 :  380.8499 
+#> Model cost at call  125 :  379.1403 
+#> Model cost at call  127 :  379.1402 
+#> Model cost at call  132 :  376.4962 
+#> Model cost at call  133 :  373.0958 
+#> Model cost at call  134 :  365.247 
+#> Model cost at call  137 :  365.2469 
+#> Model cost at call  142 :  360.8231 
+#> Model cost at call  143 :  360.8231 
+#> Model cost at call  146 :  360.8231 
+#> Model cost at call  148 :  360.8231 
+#> Model cost at call  149 :  358.3976 
+#> Model cost at call  152 :  358.3976 
+#> Model cost at call  154 :  358.3976 
+#> Model cost at call  156 :  355.9066 
+#> Model cost at call  157 :  355.9066 
+#> Model cost at call  163 :  354.3386 
+#> Model cost at call  164 :  353.6335 
+#> Model cost at call  172 :  353.2094 
+#> Model cost at call  173 :  353.2094 
+#> Model cost at call  174 :  353.2093 
+#> Model cost at call  177 :  353.2093 
+#> Model cost at call  178 :  353.2093 
+#> Model cost at call  179 :  352.6641 
+#> Model cost at call  182 :  352.6641 
+#> Model cost at call  183 :  352.6641 
+#> Model cost at call  186 :  352.4908 
+#> Model cost at call  187 :  352.4429 
+#> Model cost at call  195 :  352.3246 
+#> Model cost at call  203 :  352.2858 
+#> Model cost at call  204 :  352.2858 
+#> Model cost at call  205 :  352.2858 
+#> Model cost at call  206 :  352.2858 
+#> Model cost at call  207 :  352.2858 
+#> Model cost at call  210 :  352.2332 
+#> Model cost at call  211 :  352.2081 
+#> Model cost at call  214 :  352.2081 
+#> Model cost at call  216 :  352.2081 
+#> Model cost at call  218 :  352.2049 
+#> Model cost at call  219 :  352.2049 
+#> Model cost at call  220 :  352.2049 
+#> Model cost at call  226 :  352.2048 
+#> Model cost at call  228 :  352.2048 
+#> Model cost at call  231 :  352.2048 
+#> Model cost at call  232 :  352.2048 
+#> Model cost at call  238 :  352.2048 
+#> Model cost at call  239 :  352.2048 
+#> Model cost at call  251 :  352.2048 
+#> Model cost at call  264 :  352.2048 
+#> Model cost at call  283 :  352.2048 
+#> Model cost at call  284 :  352.2048 
+#> Model cost at call  285 :  352.2048 
+#> Model cost at call  286 :  352.2048 
+#> Optimisation by method Port successfully terminated.
# Use starting parameters from parent only SFORB fit (not really needed in this case)
+fit.SFORB = mkinfit("SFORB", FOCUS_2006_D)
#> Model cost at call  1 :  10426.65 
+#> Model cost at call  3 :  10426.65 
+#> Model cost at call  6 :  1995.326 
+#> Model cost at call  7 :  1995.322 
+#> Model cost at call  8 :  1995.14 
+#> Model cost at call  11 :  718.5568 
+#> Model cost at call  12 :  718.5566 
+#> Model cost at call  13 :  718.5563 
+#> Model cost at call  16 :  408.9208 
+#> Model cost at call  17 :  408.9204 
+#> Model cost at call  18 :  408.9204 
+#> Model cost at call  20 :  408.9203 
+#> Model cost at call  21 :  402.7935 
+#> Model cost at call  22 :  402.793 
+#> Model cost at call  26 :  202.0443 
+#> Model cost at call  28 :  202.0443 
+#> Model cost at call  30 :  202.0443 
+#> Model cost at call  31 :  196.438 
+#> Model cost at call  36 :  196.1947 
+#> Model cost at call  37 :  196.1947 
+#> Model cost at call  41 :  192.9338 
+#> Model cost at call  43 :  192.9338 
+#> Model cost at call  45 :  192.9338 
+#> Model cost at call  46 :  191.6452 
+#> Model cost at call  47 :  191.6452 
+#> Model cost at call  51 :  188.9328 
+#> Model cost at call  54 :  188.9328 
+#> Model cost at call  55 :  188.9328 
+#> Model cost at call  56 :  183.6499 
+#> Model cost at call  59 :  183.6499 
+#> Model cost at call  62 :  181.9039 
+#> Model cost at call  67 :  179.0543 
+#> Model cost at call  68 :  179.0543 
+#> Model cost at call  69 :  179.0543 
+#> Model cost at call  70 :  179.0543 
+#> Model cost at call  72 :  176.749 
+#> Model cost at call  73 :  176.2321 
+#> Model cost at call  74 :  176.232 
+#> Model cost at call  75 :  176.232 
+#> Model cost at call  76 :  176.232 
+#> Model cost at call  78 :  175.3914 
+#> Model cost at call  79 :  175.3914 
+#> Model cost at call  81 :  175.3913 
+#> Model cost at call  83 :  174.6257 
+#> Model cost at call  84 :  174.6257 
+#> Model cost at call  89 :  174.1476 
+#> Model cost at call  92 :  174.1476 
+#> Model cost at call  93 :  174.1476 
+#> Model cost at call  94 :  173.8512 
+#> Model cost at call  99 :  173.6987 
+#> Model cost at call  104 :  173.6813 
+#> Model cost at call  105 :  173.6813 
+#> Model cost at call  106 :  173.6813 
+#> Model cost at call  107 :  173.6813 
+#> Model cost at call  108 :  173.6813 
+#> Model cost at call  109 :  173.6802 
+#> Model cost at call  110 :  173.6802 
+#> Model cost at call  111 :  173.6802 
+#> Model cost at call  112 :  173.6802 
+#> Model cost at call  113 :  173.6802 
+#> Model cost at call  114 :  173.6799 
+#> Model cost at call  116 :  173.6799 
+#> Model cost at call  118 :  173.6799 
+#> Model cost at call  119 :  173.6799 
+#> Model cost at call  120 :  173.6799 
+#> Model cost at call  129 :  173.6799 
+#> Model cost at call  141 :  173.6799 
+#> Optimisation by method Port successfully terminated.
fit.SFORB_SFO <- mkinfit(SFORB_SFO, FOCUS_2006_D, parms.ini = fit.SFORB$bparms.ode)
#> Model cost at call  1 :  18365.33 
+#> Model cost at call  2 :  18365.33 
+#> Model cost at call  8 :  11666.4 
+#> Model cost at call  9 :  10992.15 
+#> Model cost at call  10 :  10992.13 
+#> Model cost at call  11 :  10991.95 
+#> Model cost at call  12 :  10991.17 
+#> Model cost at call  14 :  10990.65 
+#> Model cost at call  17 :  3940.801 
+#> Model cost at call  20 :  3940.8 
+#> Model cost at call  22 :  3940.798 
+#> Model cost at call  24 :  3241.199 
+#> Model cost at call  27 :  3241.198 
+#> Model cost at call  30 :  3241.192 
+#> Model cost at call  31 :  1518.749 
+#> Model cost at call  37 :  1518.747 
+#> Model cost at call  39 :  1091.836 
+#> Model cost at call  42 :  1091.835 
+#> Model cost at call  43 :  1091.835 
+#> Model cost at call  44 :  1091.804 
+#> Model cost at call  46 :  927.8538 
+#> Model cost at call  49 :  927.8529 
+#> Model cost at call  53 :  638.102 
+#> Model cost at call  56 :  638.1019 
+#> Model cost at call  58 :  638.1018 
+#> Model cost at call  61 :  560.4352 
+#> Model cost at call  62 :  560.435 
+#> Model cost at call  63 :  560.4327 
+#> Model cost at call  68 :  423.9629 
+#> Model cost at call  69 :  423.9629 
+#> Model cost at call  70 :  423.9629 
+#> Model cost at call  71 :  423.9628 
+#> Model cost at call  73 :  423.9628 
+#> Model cost at call  75 :  395.8015 
+#> Model cost at call  78 :  395.8013 
+#> Model cost at call  79 :  395.8013 
+#> Model cost at call  83 :  365.6975 
+#> Model cost at call  84 :  365.6975 
+#> Model cost at call  88 :  365.6975 
+#> Model cost at call  91 :  362.9843 
+#> Model cost at call  93 :  362.9843 
+#> Model cost at call  98 :  361.5506 
+#> Model cost at call  99 :  361.5506 
+#> Model cost at call  100 :  361.5505 
+#> Model cost at call  105 :  359.0492 
+#> Model cost at call  106 :  359.0492 
+#> Model cost at call  112 :  357.6574 
+#> Model cost at call  113 :  357.6574 
+#> Model cost at call  114 :  357.6574 
+#> Model cost at call  115 :  357.6574 
+#> Model cost at call  119 :  355.4518 
+#> Model cost at call  120 :  355.4518 
+#> Model cost at call  127 :  354.9045 
+#> Model cost at call  129 :  354.9045 
+#> Model cost at call  131 :  354.9045 
+#> Model cost at call  134 :  354.4168 
+#> Model cost at call  135 :  354.4168 
+#> Model cost at call  137 :  354.4167 
+#> Model cost at call  141 :  353.7901 
+#> Model cost at call  142 :  353.7901 
+#> Model cost at call  143 :  353.7899 
+#> Model cost at call  149 :  353.3233 
+#> Model cost at call  151 :  353.3233 
+#> Model cost at call  154 :  353.3233 
+#> Model cost at call  156 :  353.2939 
+#> Model cost at call  158 :  353.2938 
+#> Model cost at call  159 :  353.2938 
+#> Model cost at call  160 :  353.2938 
+#> Model cost at call  163 :  353.0571 
+#> Model cost at call  165 :  353.0571 
+#> Model cost at call  170 :  352.9457 
+#> Model cost at call  171 :  352.7458 
+#> Model cost at call  173 :  352.7457 
+#> Model cost at call  178 :  352.6377 
+#> Model cost at call  180 :  352.6377 
+#> Model cost at call  183 :  352.6377 
+#> Model cost at call  185 :  352.5377 
+#> Model cost at call  187 :  352.5377 
+#> Model cost at call  188 :  352.5377 
+#> Model cost at call  191 :  352.5377 
+#> Model cost at call  193 :  352.4479 
+#> Model cost at call  195 :  352.4479 
+#> Model cost at call  198 :  352.4479 
+#> Model cost at call  200 :  352.4021 
+#> Model cost at call  202 :  352.4021 
+#> Model cost at call  205 :  352.4021 
+#> Model cost at call  207 :  352.3465 
+#> Model cost at call  210 :  352.3465 
+#> Model cost at call  214 :  352.3031 
+#> Model cost at call  216 :  352.3031 
+#> Model cost at call  221 :  352.2632 
+#> Model cost at call  223 :  352.2632 
+#> Model cost at call  228 :  352.2367 
+#> Model cost at call  230 :  352.2367 
+#> Model cost at call  231 :  352.2367 
+#> Model cost at call  233 :  352.2367 
+#> Model cost at call  235 :  352.215 
+#> Model cost at call  238 :  352.215 
+#> Model cost at call  239 :  352.215 
+#> Model cost at call  242 :  352.207 
+#> Model cost at call  245 :  352.207 
+#> Model cost at call  250 :  352.2053 
+#> Model cost at call  251 :  352.2053 
+#> Model cost at call  253 :  352.2053 
+#> Model cost at call  256 :  352.2053 
+#> Model cost at call  258 :  352.2053 
+#> Model cost at call  259 :  352.2052 
+#> Model cost at call  260 :  352.2052 
+#> Model cost at call  263 :  352.2052 
+#> Model cost at call  271 :  352.2048 
+#> Model cost at call  273 :  352.2048 
+#> Model cost at call  274 :  352.2048 
+#> Model cost at call  281 :  352.2048 
+#> Model cost at call  282 :  352.2048 
+#> Model cost at call  286 :  352.2048 
+#> Model cost at call  289 :  352.2048 
+#> Model cost at call  294 :  352.2048 
+#> Model cost at call  296 :  352.2048 
+#> Model cost at call  300 :  352.2048 
+#> Model cost at call  307 :  352.2048 
+#> Model cost at call  325 :  352.2048 
+#> Model cost at call  331 :  352.2048 
+#> Model cost at call  333 :  352.2048 
+#> Optimisation by method Port successfully terminated.

+
+
+# Weighted fits, including IRLS
+SFO_SFO.ff <- mkinmod(parent = mkinsub("SFO", "m1"),
+                      m1 = mkinsub("SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
f.noweight <- mkinfit(SFO_SFO.ff, FOCUS_2006_D)
#> Model cost at call  1 :  15156.12 
+#> Model cost at call  2 :  15156.12 
+#> Model cost at call  6 :  8243.644 
+#> Model cost at call  12 :  6290.714 
+#> Model cost at call  13 :  6290.684 
+#> Model cost at call  15 :  6290.453 
+#> Model cost at call  18 :  1700.75 
+#> Model cost at call  20 :  1700.612 
+#> Model cost at call  24 :  1190.923 
+#> Model cost at call  26 :  1190.922 
+#> Model cost at call  29 :  1017.417 
+#> Model cost at call  31 :  1017.417 
+#> Model cost at call  33 :  1017.416 
+#> Model cost at call  34 :  644.0471 
+#> Model cost at call  36 :  644.0469 
+#> Model cost at call  38 :  644.0468 
+#> Model cost at call  39 :  590.5024 
+#> Model cost at call  41 :  590.5021 
+#> Model cost at call  43 :  590.5015 
+#> Model cost at call  44 :  543.2187 
+#> Model cost at call  45 :  543.2183 
+#> Model cost at call  46 :  543.2182 
+#> Model cost at call  50 :  391.348 
+#> Model cost at call  51 :  391.3479 
+#> Model cost at call  56 :  386.4789 
+#> Model cost at call  58 :  386.4789 
+#> Model cost at call  60 :  386.4779 
+#> Model cost at call  61 :  384.0686 
+#> Model cost at call  63 :  384.0686 
+#> Model cost at call  66 :  382.7812 
+#> Model cost at call  68 :  382.7812 
+#> Model cost at call  70 :  382.7812 
+#> Model cost at call  71 :  378.9272 
+#> Model cost at call  73 :  378.9272 
+#> Model cost at call  75 :  378.9272 
+#> Model cost at call  76 :  377.4846 
+#> Model cost at call  78 :  377.4846 
+#> Model cost at call  81 :  375.9738 
+#> Model cost at call  83 :  375.9738 
+#> Model cost at call  86 :  375.3387 
+#> Model cost at call  88 :  375.3387 
+#> Model cost at call  91 :  374.5774 
+#> Model cost at call  93 :  374.5774 
+#> Model cost at call  95 :  374.5774 
+#> Model cost at call  96 :  373.5447 
+#> Model cost at call  100 :  373.5446 
+#> Model cost at call  102 :  373.2643 
+#> Model cost at call  104 :  373.2643 
+#> Model cost at call  107 :  372.6799 
+#> Model cost at call  111 :  372.6798 
+#> Model cost at call  114 :  372.6325 
+#> Model cost at call  116 :  372.6325 
+#> Model cost at call  119 :  372.6159 
+#> Model cost at call  121 :  372.6159 
+#> Model cost at call  123 :  372.6159 
+#> Model cost at call  124 :  372.5845 
+#> Model cost at call  126 :  372.5845 
+#> Model cost at call  129 :  372.5375 
+#> Model cost at call  130 :  372.4771 
+#> Model cost at call  131 :  372.2008 
+#> Model cost at call  132 :  371.4923 
+#> Model cost at call  134 :  371.4923 
+#> Model cost at call  137 :  371.3022 
+#> Model cost at call  139 :  371.3022 
+#> Model cost at call  143 :  371.2271 
+#> Model cost at call  144 :  371.2271 
+#> Model cost at call  148 :  371.2202 
+#> Model cost at call  149 :  371.215 
+#> Model cost at call  152 :  371.215 
+#> Model cost at call  154 :  371.2136 
+#> Model cost at call  155 :  371.2136 
+#> Model cost at call  156 :  371.2136 
+#> Model cost at call  160 :  371.2134 
+#> Model cost at call  164 :  371.2134 
+#> Model cost at call  167 :  371.2134 
+#> Optimisation by method Port successfully terminated.
summary(f.noweight)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:47 2016 
+#> Date of summary: Fri Nov 18 15:19:47 2016 
+#> 
+#> 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 185 model solutions performed in 0.748 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
+#> 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       99.60000    1.61400 96.3300 102.9000
+#> log_k_parent   -2.31600    0.04187 -2.4010  -2.2310
+#> log_k_m1       -5.24800    0.13610 -5.5230  -4.9720
+#> f_parent_ilr_1  0.04096    0.06477 -0.0904   0.1723
+#> 
+#> Parameter correlation:
+#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
+#> parent_0         1.0000       0.5178  -0.1701        -0.5489
+#> log_k_parent     0.5178       1.0000  -0.3285        -0.5451
+#> log_k_m1        -0.1701      -0.3285   1.0000         0.7466
+#> f_parent_ilr_1  -0.5489      -0.5451   0.7466         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        0.098700  23.880 5.701e-24  0.090660 1.074e-01
+#> k_m1            0.005261   7.349 5.758e-09  0.003992 6.933e-03
+#> f_parent_to_m1  0.514500  22.490 4.374e-23  0.468100 5.606e-01
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   6.398       4 15
+#> parent     6.459       2  7
+#> m1         4.690       2  8
+#> 
+#> Resulting formation fractions:
+#>                 ff
+#> parent_m1   0.5145
+#> parent_sink 0.4855
+#> 
+#> Estimated disappearance times:
+#>           DT50   DT90
+#> parent   7.023  23.33
+#> m1     131.761 437.70
+#> 
+#> Data:
+#>  time variable observed predicted   residual
+#>     0   parent    99.46 9.960e+01 -1.385e-01
+#>     0   parent   102.04 9.960e+01  2.442e+00
+#>     1   parent    93.50 9.024e+01  3.262e+00
+#>     1   parent    92.50 9.024e+01  2.262e+00
+#>     3   parent    63.23 7.407e+01 -1.084e+01
+#>     3   parent    68.99 7.407e+01 -5.083e+00
+#>     7   parent    52.32 4.991e+01  2.408e+00
+#>     7   parent    55.13 4.991e+01  5.218e+00
+#>    14   parent    27.27 2.501e+01  2.257e+00
+#>    14   parent    26.64 2.501e+01  1.627e+00
+#>    21   parent    11.50 1.253e+01 -1.035e+00
+#>    21   parent    11.64 1.253e+01 -8.946e-01
+#>    35   parent     2.85 3.148e+00 -2.979e-01
+#>    35   parent     2.91 3.148e+00 -2.379e-01
+#>    50   parent     0.69 7.162e-01 -2.624e-02
+#>    50   parent     0.63 7.162e-01 -8.624e-02
+#>    75   parent     0.05 6.074e-02 -1.074e-02
+#>    75   parent     0.06 6.074e-02 -7.381e-04
+#>   100   parent       NA 5.151e-03         NA
+#>   100   parent       NA 5.151e-03         NA
+#>   120   parent       NA 7.155e-04         NA
+#>   120   parent       NA 7.155e-04         NA
+#>     0       m1     0.00 0.000e+00  0.000e+00
+#>     0       m1     0.00 0.000e+00  0.000e+00
+#>     1       m1     4.84 4.803e+00  3.704e-02
+#>     1       m1     5.64 4.803e+00  8.370e-01
+#>     3       m1    12.91 1.302e+01 -1.140e-01
+#>     3       m1    12.96 1.302e+01 -6.400e-02
+#>     7       m1    22.97 2.504e+01 -2.075e+00
+#>     7       m1    24.47 2.504e+01 -5.748e-01
+#>    14       m1    41.69 3.669e+01  5.000e+00
+#>    14       m1    33.21 3.669e+01 -3.480e+00
+#>    21       m1    44.37 4.165e+01  2.717e+00
+#>    21       m1    46.44 4.165e+01  4.787e+00
+#>    35       m1    41.22 4.331e+01 -2.093e+00
+#>    35       m1    37.95 4.331e+01 -5.363e+00
+#>    50       m1    41.19 4.122e+01 -2.831e-02
+#>    50       m1    40.01 4.122e+01 -1.208e+00
+#>    75       m1    40.09 3.645e+01  3.643e+00
+#>    75       m1    33.85 3.645e+01 -2.597e+00
+#>   100       m1    31.04 3.198e+01 -9.416e-01
+#>   100       m1    33.13 3.198e+01  1.148e+00
+#>   120       m1    25.15 2.879e+01 -3.640e+00
+#>   120       m1    33.31 2.879e+01  4.520e+00
f.irls <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, reweight.method = "obs")
#> Model cost at call  1 :  15156.12 
+#> Model cost at call  2 :  15156.12 
+#> Model cost at call  6 :  8243.644 
+#> Model cost at call  12 :  6290.714 
+#> Model cost at call  13 :  6290.684 
+#> Model cost at call  15 :  6290.453 
+#> Model cost at call  18 :  1700.75 
+#> Model cost at call  20 :  1700.612 
+#> Model cost at call  24 :  1190.923 
+#> Model cost at call  26 :  1190.922 
+#> Model cost at call  29 :  1017.417 
+#> Model cost at call  31 :  1017.417 
+#> Model cost at call  33 :  1017.416 
+#> Model cost at call  34 :  644.0471 
+#> Model cost at call  36 :  644.0469 
+#> Model cost at call  38 :  644.0468 
+#> Model cost at call  39 :  590.5024 
+#> Model cost at call  41 :  590.5021 
+#> Model cost at call  43 :  590.5015 
+#> Model cost at call  44 :  543.2187 
+#> Model cost at call  45 :  543.2183 
+#> Model cost at call  46 :  543.2182 
+#> Model cost at call  50 :  391.348 
+#> Model cost at call  51 :  391.3479 
+#> Model cost at call  56 :  386.4789 
+#> Model cost at call  58 :  386.4789 
+#> Model cost at call  60 :  386.4779 
+#> Model cost at call  61 :  384.0686 
+#> Model cost at call  63 :  384.0686 
+#> Model cost at call  66 :  382.7812 
+#> Model cost at call  68 :  382.7812 
+#> Model cost at call  70 :  382.7812 
+#> Model cost at call  71 :  378.9272 
+#> Model cost at call  73 :  378.9272 
+#> Model cost at call  75 :  378.9272 
+#> Model cost at call  76 :  377.4846 
+#> Model cost at call  78 :  377.4846 
+#> Model cost at call  81 :  375.9738 
+#> Model cost at call  83 :  375.9738 
+#> Model cost at call  86 :  375.3387 
+#> Model cost at call  88 :  375.3387 
+#> Model cost at call  91 :  374.5774 
+#> Model cost at call  93 :  374.5774 
+#> Model cost at call  95 :  374.5774 
+#> Model cost at call  96 :  373.5447 
+#> Model cost at call  100 :  373.5446 
+#> Model cost at call  102 :  373.2643 
+#> Model cost at call  104 :  373.2643 
+#> Model cost at call  107 :  372.6799 
+#> Model cost at call  111 :  372.6798 
+#> Model cost at call  114 :  372.6325 
+#> Model cost at call  116 :  372.6325 
+#> Model cost at call  119 :  372.6159 
+#> Model cost at call  121 :  372.6159 
+#> Model cost at call  123 :  372.6159 
+#> Model cost at call  124 :  372.5845 
+#> Model cost at call  126 :  372.5845 
+#> Model cost at call  129 :  372.5375 
+#> Model cost at call  130 :  372.4771 
+#> Model cost at call  131 :  372.2008 
+#> Model cost at call  132 :  371.4923 
+#> Model cost at call  134 :  371.4923 
+#> Model cost at call  137 :  371.3022 
+#> Model cost at call  139 :  371.3022 
+#> Model cost at call  143 :  371.2271 
+#> Model cost at call  144 :  371.2271 
+#> Model cost at call  148 :  371.2202 
+#> Model cost at call  149 :  371.215 
+#> Model cost at call  152 :  371.215 
+#> Model cost at call  154 :  371.2136 
+#> Model cost at call  155 :  371.2136 
+#> Model cost at call  156 :  371.2136 
+#> Model cost at call  160 :  371.2134 
+#> Model cost at call  164 :  371.2134 
+#> Model cost at call  167 :  371.2134 
+#> IRLS based on variance estimates for each observed variable
+#> Initial variance estimates are:
+#>    parent        m1 
+#> 11.552581  7.421226 
+#> Model cost at call  186 :  40 
+#> Model cost at call  188 :  40 
+#> Model cost at call  194 :  39.99562 
+#> Model cost at call  195 :  39.99562 
+#> Model cost at call  201 :  39.9956 
+#> Model cost at call  203 :  39.99528 
+#> Model cost at call  205 :  39.99528 
+#> Model cost at call  207 :  39.99528 
+#> Model cost at call  209 :  39.99515 
+#> Model cost at call  211 :  39.99515 
+#> Model cost at call  214 :  39.99515 
+#> Model cost at call  215 :  39.99505 
+#> Model cost at call  217 :  39.99505 
+#> Model cost at call  219 :  39.99505 
+#> Model cost at call  220 :  39.99489 
+#> Model cost at call  222 :  39.99489 
+#> Model cost at call  224 :  39.99489 
+#> Model cost at call  225 :  39.99479 
+#> Model cost at call  227 :  39.99479 
+#> Model cost at call  231 :  39.99467 
+#> Model cost at call  234 :  39.99467 
+#> Model cost at call  235 :  39.99467 
+#> Model cost at call  236 :  39.99458 
+#> Model cost at call  238 :  39.99458 
+#> Model cost at call  239 :  39.99458 
+#> Model cost at call  241 :  39.99452 
+#> Model cost at call  242 :  39.99444 
+#> Model cost at call  243 :  39.99433 
+#> Model cost at call  245 :  39.99433 
+#> Model cost at call  248 :  39.99383 
+#> Model cost at call  250 :  39.99383 
+#> Model cost at call  251 :  39.99383 
+#> Model cost at call  252 :  39.99383 
+#> Model cost at call  253 :  39.9935 
+#> Model cost at call  254 :  39.99309 
+#> Model cost at call  256 :  39.99309 
+#> Model cost at call  261 :  39.99295 
+#> Model cost at call  264 :  39.99295 
+#> Model cost at call  267 :  39.99281 
+#> Model cost at call  272 :  39.99281 
+#> Model cost at call  273 :  39.99278 
+#> Model cost at call  276 :  39.99278 
+#> Model cost at call  278 :  39.99278 
+#> Model cost at call  279 :  39.99278 
+#> Model cost at call  281 :  39.99278 
+#> Model cost at call  283 :  39.99278 
+#> Model cost at call  286 :  39.99278 
+#> Model cost at call  289 :  39.99278 
+#> Model cost at call  290 :  39.99278 
+#> Iteration 1 yields variance estimates:
+#>    parent        m1 
+#> 11.573172  7.407968 
+#> Sum of squared differences to last variance estimates: 1.5e-05 
+#> Iteration 2 yields variance estimates:
+#>    parent        m1 
+#> 11.573405  7.407846 
+#> Sum of squared differences to last variance estimates: 1.7e-09 
+#> Optimisation by method Port successfully terminated.
summary(f.irls)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:50 2016 
+#> Date of summary: Fri Nov 18 15:19:50 2016 
+#> 
+#> 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 486 model solutions performed in 2.052 s
+#> 
+#> Weighting: none then iterative reweighting method obs
+#> 
+#> 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 8.183e-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 8.487e-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
+#>     0   parent    99.46 9.967e+01 -2.122e-01 3.402
+#>     0   parent   102.04 9.967e+01  2.368e+00 3.402
+#>     1   parent    93.50 9.027e+01  3.228e+00 3.402
+#>     1   parent    92.50 9.027e+01  2.228e+00 3.402
+#>     3   parent    63.23 7.405e+01 -1.082e+01 3.402
+#>     3   parent    68.99 7.405e+01 -5.056e+00 3.402
+#>     7   parent    52.32 4.982e+01  2.499e+00 3.402
+#>     7   parent    55.13 4.982e+01  5.309e+00 3.402
+#>    14   parent    27.27 2.490e+01  2.367e+00 3.402
+#>    14   parent    26.64 2.490e+01  1.737e+00 3.402
+#>    21   parent    11.50 1.245e+01 -9.477e-01 3.402
+#>    21   parent    11.64 1.245e+01 -8.077e-01 3.402
+#>    35   parent     2.85 3.110e+00 -2.600e-01 3.402
+#>    35   parent     2.91 3.110e+00 -2.000e-01 3.402
+#>    50   parent     0.69 7.037e-01 -1.375e-02 3.402
+#>    50   parent     0.63 7.037e-01 -7.375e-02 3.402
+#>    75   parent     0.05 5.913e-02 -9.134e-03 3.402
+#>    75   parent     0.06 5.913e-02  8.661e-04 3.402
+#>   100   parent       NA 4.969e-03         NA 3.402
+#>   100   parent       NA 4.969e-03         NA 3.402
+#>   120   parent       NA 6.852e-04         NA 3.402
+#>   120   parent       NA 6.852e-04         NA 3.402
+#>     0       m1     0.00 0.000e+00  0.000e+00 2.722
+#>     0       m1     0.00 0.000e+00  0.000e+00 2.722
+#>     1       m1     4.84 4.813e+00  2.672e-02 2.722
+#>     1       m1     5.64 4.813e+00  8.267e-01 2.722
+#>     3       m1    12.91 1.305e+01 -1.378e-01 2.722
+#>     3       m1    12.96 1.305e+01 -8.779e-02 2.722
+#>     7       m1    22.97 2.508e+01 -2.106e+00 2.722
+#>     7       m1    24.47 2.508e+01 -6.061e-01 2.722
+#>    14       m1    41.69 3.671e+01  4.983e+00 2.722
+#>    14       m1    33.21 3.671e+01 -3.497e+00 2.722
+#>    21       m1    44.37 4.165e+01  2.719e+00 2.722
+#>    21       m1    46.44 4.165e+01  4.789e+00 2.722
+#>    35       m1    41.22 4.329e+01 -2.069e+00 2.722
+#>    35       m1    37.95 4.329e+01 -5.339e+00 2.722
+#>    50       m1    41.19 4.119e+01 -3.388e-03 2.722
+#>    50       m1    40.01 4.119e+01 -1.183e+00 2.722
+#>    75       m1    40.09 3.644e+01  3.652e+00 2.722
+#>    75       m1    33.85 3.644e+01 -2.588e+00 2.722
+#>   100       m1    31.04 3.199e+01 -9.497e-01 2.722
+#>   100       m1    33.13 3.199e+01  1.140e+00 2.722
+#>   120       m1    25.15 2.881e+01 -3.659e+00 2.722
+#>   120       m1    33.31 2.881e+01  4.501e+00 2.722
f.w.mean <- mkinfit(SFO_SFO.ff, FOCUS_2006_D, weight = "mean")
#> Model cost at call  1 :  19.80132 
+#> Model cost at call  2 :  19.80132 
+#> Model cost at call  6 :  10.68776 
+#> Model cost at call  12 :  7.14353 
+#> Model cost at call  13 :  7.143529 
+#> Model cost at call  15 :  7.143511 
+#> Model cost at call  18 :  2.189024 
+#> Model cost at call  20 :  2.189019 
+#> Model cost at call  23 :  1.587262 
+#> Model cost at call  25 :  1.587261 
+#> Model cost at call  26 :  1.58726 
+#> Model cost at call  28 :  1.036794 
+#> Model cost at call  29 :  1.036794 
+#> Model cost at call  30 :  1.036793 
+#> Model cost at call  34 :  0.4939937 
+#> Model cost at call  35 :  0.4939937 
+#> Model cost at call  38 :  0.4939936 
+#> Model cost at call  39 :  0.4018506 
+#> Model cost at call  43 :  0.4018505 
+#> Model cost at call  45 :  0.3797853 
+#> Model cost at call  51 :  0.3669779 
+#> Model cost at call  55 :  0.3669778 
+#> Model cost at call  56 :  0.3585654 
+#> Model cost at call  57 :  0.3533252 
+#> Model cost at call  62 :  0.3502505 
+#> Model cost at call  64 :  0.3502505 
+#> Model cost at call  66 :  0.3502505 
+#> Model cost at call  67 :  0.3501535 
+#> Model cost at call  72 :  0.3501187 
+#> Model cost at call  74 :  0.3501187 
+#> Model cost at call  75 :  0.3501187 
+#> Model cost at call  77 :  0.3500378 
+#> Model cost at call  79 :  0.3500378 
+#> Model cost at call  83 :  0.349831 
+#> Model cost at call  88 :  0.3494286 
+#> Model cost at call  93 :  0.3488101 
+#> Model cost at call  98 :  0.3481444 
+#> Model cost at call  103 :  0.3478528 
+#> Model cost at call  108 :  0.3478092 
+#> Model cost at call  109 :  0.3478092 
+#> Model cost at call  113 :  0.347807 
+#> Model cost at call  116 :  0.347807 
+#> Model cost at call  117 :  0.347807 
+#> Model cost at call  119 :  0.347807 
+#> Model cost at call  120 :  0.347807 
+#> Model cost at call  125 :  0.347807 
+#> Model cost at call  126 :  0.347807 
+#> Model cost at call  128 :  0.347807 
+#> Model cost at call  137 :  0.347807 
+#> Model cost at call  148 :  0.347807 
+#> Model cost at call  152 :  0.347807 
+#> Model cost at call  154 :  0.347807 
+#> Optimisation by method Port successfully terminated.
summary(f.w.mean)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:50 2016 
+#> Date of summary: Fri Nov 18 15:19:50 2016 
+#> 
+#> 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 155 model solutions performed in 0.636 s
+#> 
+#> Weighting: mean
+#> 
+#> 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        99.7300    1.93200 95.81000 103.6000
+#> log_k_parent    -2.3090    0.04837 -2.40700  -2.2110
+#> log_k_m1        -5.2550    0.12070 -5.49900  -5.0100
+#> f_parent_ilr_1   0.0354    0.06344 -0.09327   0.1641
+#> 
+#> Parameter correlation:
+#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
+#> parent_0         1.0000       0.5004  -0.2143        -0.6514
+#> log_k_parent     0.5004       1.0000  -0.4282        -0.6383
+#> log_k_m1        -0.2143      -0.4282   1.0000         0.7390
+#> f_parent_ilr_1  -0.6514      -0.6383   0.7390         1.0000
+#> 
+#> Residual standard error: 0.09829 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       99.730000  51.630 1.166e-35 95.81000 1.036e+02
+#> k_parent        0.099360  20.670 7.304e-22  0.09007 1.096e-01
+#> k_m1            0.005224   8.287 3.649e-10  0.00409 6.672e-03
+#> f_parent_to_m1  0.512500  22.860 2.497e-23  0.46710 5.578e-01
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   6.401       4 15
+#> parent     6.473       2  7
+#> m1         4.671       2  8
+#> 
+#> Resulting formation fractions:
+#>                 ff
+#> parent_m1   0.5125
+#> parent_sink 0.4875
+#> 
+#> Estimated disappearance times:
+#>           DT50   DT90
+#> parent   6.976  23.18
+#> m1     132.696 440.81
+#> 
+#> Data:
+#>  time variable observed predicted   residual
+#>     0   parent    99.46 99.730570  -0.270570
+#>     0   parent   102.04 99.730570   2.309430
+#>     1   parent    93.50 90.298055   3.201945
+#>     1   parent    92.50 90.298055   2.201945
+#>     3   parent    63.23 74.025028 -10.795028
+#>     3   parent    68.99 74.025028  -5.035028
+#>     7   parent    52.32 49.748382   2.571618
+#>     7   parent    55.13 49.748382   5.381618
+#>    14   parent    27.27 24.815876   2.454124
+#>    14   parent    26.64 24.815876   1.824124
+#>    21   parent    11.50 12.378849  -0.878849
+#>    21   parent    11.64 12.378849  -0.738849
+#>    35   parent     2.85  3.080219  -0.230219
+#>    35   parent     2.91  3.080219  -0.170219
+#>    50   parent     0.69  0.693958  -0.003958
+#>    50   parent     0.63  0.693958  -0.063958
+#>    75   parent     0.05  0.057888  -0.007888
+#>    75   parent     0.06  0.057888   0.002112
+#>   100   parent       NA  0.004829         NA
+#>   100   parent       NA  0.004829         NA
+#>   120   parent       NA  0.000662         NA
+#>   120   parent       NA  0.000662         NA
+#>     0       m1     0.00  0.000000   0.000000
+#>     0       m1     0.00  0.000000   0.000000
+#>     1       m1     4.84  4.821488   0.018512
+#>     1       m1     5.64  4.821488   0.818512
+#>     3       m1    12.91 13.066692  -0.156692
+#>     3       m1    12.96 13.066692  -0.106692
+#>     7       m1    22.97 25.101058  -2.131058
+#>     7       m1    24.47 25.101058  -0.631058
+#>    14       m1    41.69 36.720923   4.969077
+#>    14       m1    33.21 36.720923  -3.510923
+#>    21       m1    44.37 41.648353   2.721647
+#>    21       m1    46.44 41.648353   4.791647
+#>    35       m1    41.22 43.269225  -2.049225
+#>    35       m1    37.95 43.269225  -5.319225
+#>    50       m1    41.19 41.173639   0.016361
+#>    50       m1    40.01 41.173639  -1.163639
+#>    75       m1    40.09 36.431224   3.658776
+#>    75       m1    33.85 36.431224  -2.581224
+#>   100       m1    31.04 31.996124  -0.956124
+#>   100       m1    33.13 31.996124   1.133876
+#>   120       m1    25.15 28.824128  -3.674128
+#>   120       m1    33.31 28.824128   4.485872
f.w.value <- mkinfit(SFO_SFO.ff, subset(FOCUS_2006_D, value != 0), err = "value")
#> Model cost at call  1 :  11.21571 
+#> Model cost at call  2 :  11.21571 
+#> Model cost at call  3 :  11.21571 
+#> Model cost at call  8 :  11.12803 
+#> Model cost at call  10 :  11.128 
+#> Model cost at call  13 :  10.88016 
+#> Model cost at call  15 :  10.88016 
+#> Model cost at call  18 :  10.58819 
+#> Model cost at call  20 :  10.58819 
+#> Model cost at call  23 :  9.71699 
+#> Model cost at call  24 :  7.794026 
+#> Model cost at call  26 :  7.794026 
+#> Model cost at call  31 :  6.89734 
+#> Model cost at call  33 :  6.897337 
+#> Model cost at call  36 :  5.2239 
+#> Model cost at call  37 :  3.357735 
+#> Model cost at call  41 :  3.357733 
+#> Model cost at call  44 :  2.982323 
+#> Model cost at call  46 :  2.982322 
+#> Model cost at call  49 :  2.703946 
+#> Model cost at call  50 :  2.080395 
+#> Model cost at call  55 :  0.5307591 
+#> Model cost at call  56 :  0.5307591 
+#> Model cost at call  57 :  0.5307591 
+#> Model cost at call  59 :  0.5307584 
+#> Model cost at call  60 :  0.3240066 
+#> Model cost at call  61 :  0.3240066 
+#> Model cost at call  64 :  0.3240066 
+#> Model cost at call  65 :  0.2601108 
+#> Model cost at call  70 :  0.2414055 
+#> Model cost at call  74 :  0.2414055 
+#> Model cost at call  75 :  0.2404251 
+#> Model cost at call  80 :  0.2404087 
+#> Model cost at call  82 :  0.2404087 
+#> Model cost at call  85 :  0.2404054 
+#> Model cost at call  88 :  0.2404054 
+#> Model cost at call  92 :  0.2403931 
+#> Model cost at call  93 :  0.2403784 
+#> Model cost at call  98 :  0.2403784 
+#> Model cost at call  99 :  0.2403322 
+#> Model cost at call  104 :  0.2402188 
+#> Model cost at call  109 :  0.2400275 
+#> Model cost at call  114 :  0.239844 
+#> Model cost at call  119 :  0.2397153 
+#> Model cost at call  120 :  0.2397153 
+#> Model cost at call  124 :  0.2396978 
+#> Model cost at call  126 :  0.2396978 
+#> Model cost at call  130 :  0.239697 
+#> Model cost at call  131 :  0.2396963 
+#> Model cost at call  133 :  0.2396963 
+#> Model cost at call  138 :  0.2396962 
+#> Model cost at call  139 :  0.2396962 
+#> Model cost at call  141 :  0.2396962 
+#> Model cost at call  144 :  0.2396962 
+#> Model cost at call  147 :  0.2396962 
+#> Model cost at call  156 :  0.2396962 
+#> Model cost at call  167 :  0.2396962 
+#> Model cost at call  169 :  0.2396962 
+#> Optimisation by method Port successfully terminated.
summary(f.w.value)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:51 2016 
+#> Date of summary: Fri Nov 18 15:19:51 2016 
+#> 
+#> 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 174 model solutions performed in 0.789 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        99.6600   2.712000 94.14000 105.2000
+#> log_k_parent    -2.2980   0.008118 -2.31500  -2.2820
+#> log_k_m1        -5.2410   0.096690 -5.43800  -5.0450
+#> f_parent_ilr_1   0.0231   0.057990 -0.09474   0.1409
+#> 
+#> Parameter correlation:
+#>                parent_0 log_k_parent log_k_m1 f_parent_ilr_1
+#> parent_0        1.00000       0.6844 -0.08687        -0.7564
+#> log_k_parent    0.68435       1.0000 -0.12694        -0.5812
+#> log_k_m1       -0.08687      -0.1269  1.00000         0.5195
+#> f_parent_ilr_1 -0.75644      -0.5812  0.51951         1.0000
+#> 
+#> Residual standard error: 0.08396 on 34 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       99.660000   36.75 2.957e-29 94.14000 1.052e+02
+#> k_parent        0.100400  123.20 5.927e-47  0.09878 1.021e-01
+#> k_m1            0.005295   10.34 2.447e-12  0.00435 6.444e-03
+#> f_parent_to_m1  0.508200   24.79 1.184e-23  0.46660 5.497e-01
+#> 
+#> Chi2 error levels in percent:
+#>          err.min n.optim df
+#> All data   6.461       4 15
+#> parent     6.520       2  7
+#> m1         4.744       2  8
+#> 
+#> Resulting formation fractions:
+#>                 ff
+#> parent_m1   0.5082
+#> parent_sink 0.4918
+#> 
+#> Estimated disappearance times:
+#>           DT50   DT90
+#> parent   6.902  22.93
+#> m1     130.916 434.89
+#> 
+#> Data:
+#>  time variable observed predicted   residual    err
+#>     0   parent    99.46  99.65571  -0.195714  99.46
+#>     0   parent   102.04  99.65571   2.384286 102.04
+#>     1   parent    93.50  90.13383   3.366170  93.50
+#>     1   parent    92.50  90.13383   2.366170  92.50
+#>     3   parent    63.23  73.73252 -10.502518  63.23
+#>     3   parent    68.99  73.73252  -4.742518  68.99
+#>     7   parent    52.32  49.34027   2.979728  52.32
+#>     7   parent    55.13  49.34027   5.789728  55.13
+#>    14   parent    27.27  24.42873   2.841271  27.27
+#>    14   parent    26.64  24.42873   2.211271  26.64
+#>    21   parent    11.50  12.09484  -0.594842  11.50
+#>    21   parent    11.64  12.09484  -0.454842  11.64
+#>    35   parent     2.85   2.96482  -0.114824   2.85
+#>    35   parent     2.91   2.96482  -0.054824   2.91
+#>    50   parent     0.69   0.65733   0.032670   0.69
+#>    50   parent     0.63   0.65733  -0.027330   0.63
+#>    75   parent     0.05   0.05339  -0.003386   0.05
+#>    75   parent     0.06   0.05339   0.006614   0.06
+#>     1       m1     4.84   4.82570   0.014301   4.84
+#>     1       m1     5.64   4.82570   0.814301   5.64
+#>     3       m1    12.91  13.06402  -0.154020  12.91
+#>     3       m1    12.96  13.06402  -0.104020  12.96
+#>     7       m1    22.97  25.04656  -2.076564  22.97
+#>     7       m1    24.47  25.04656  -0.576564  24.47
+#>    14       m1    41.69  36.53601   5.153988  41.69
+#>    14       m1    33.21  36.53601  -3.326012  33.21
+#>    21       m1    44.37  41.34639   3.023609  44.37
+#>    21       m1    46.44  41.34639   5.093609  46.44
+#>    35       m1    41.22  42.82669  -1.606690  41.22
+#>    35       m1    37.95  42.82669  -4.876690  37.95
+#>    50       m1    41.19  40.67342   0.516578  41.19
+#>    50       m1    40.01  40.67342  -0.663422  40.01
+#>    75       m1    40.09  35.91105   4.178947  40.09
+#>    75       m1    33.85  35.91105  -2.061053  33.85
+#>   100       m1    31.04  31.48161  -0.441612  31.04
+#>   100       m1    33.13  31.48161   1.648388  33.13
+#>   120       m1    25.15  28.32018  -3.170181  25.15
+#>   120       m1    33.31  28.32018   4.989819  33.31

+
+
+# 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")
#> Model cost at call  1 :  3949.676 
+#> Model cost at call  2 :  3949.676 
+#> Model cost at call  5 :  3949.676 
+#> Model cost at call  6 :  2252.859 
+#> Model cost at call  8 :  2252.858 
+#> Model cost at call  9 :  2252.826 
+#> Model cost at call  13 :  1567.343 
+#> Model cost at call  14 :  1567.342 
+#> Model cost at call  15 :  1567.333 
+#> Model cost at call  18 :  1041.524 
+#> Model cost at call  19 :  1041.522 
+#> Model cost at call  24 :  840.4649 
+#> Model cost at call  26 :  840.4646 
+#> Model cost at call  29 :  782.303 
+#> Model cost at call  31 :  782.3028 
+#> Model cost at call  34 :  664.539 
+#> Model cost at call  36 :  664.5389 
+#> Model cost at call  40 :  615.7908 
+#> Model cost at call  42 :  615.7907 
+#> Model cost at call  45 :  569.5971 
+#> Model cost at call  47 :  569.597 
+#> Model cost at call  50 :  517.3175 
+#> Model cost at call  52 :  517.3173 
+#> Model cost at call  56 :  464.8158 
+#> Model cost at call  58 :  464.8157 
+#> Model cost at call  62 :  433.0031 
+#> Model cost at call  64 :  433.003 
+#> Model cost at call  67 :  423.7407 
+#> Model cost at call  69 :  423.7406 
+#> Model cost at call  70 :  423.7392 
+#> Model cost at call  72 :  346.2781 
+#> Model cost at call  74 :  346.278 
+#> Model cost at call  75 :  346.2779 
+#> Model cost at call  78 :  334.5399 
+#> Model cost at call  80 :  334.5398 
+#> Model cost at call  83 :  324.139 
+#> Model cost at call  85 :  324.1389 
+#> Model cost at call  88 :  319.7514 
+#> Model cost at call  90 :  319.7514 
+#> Model cost at call  94 :  300.9426 
+#> Model cost at call  96 :  300.9425 
+#> Model cost at call  100 :  295.8803 
+#> Model cost at call  102 :  295.8803 
+#> Model cost at call  105 :  290.3288 
+#> Model cost at call  107 :  290.3287 
+#> Model cost at call  111 :  284.3257 
+#> Model cost at call  113 :  284.3257 
+#> Model cost at call  116 :  282.3972 
+#> Model cost at call  118 :  282.3972 
+#> Model cost at call  122 :  273.7385 
+#> Model cost at call  124 :  273.7385 
+#> Model cost at call  128 :  271.8379 
+#> Model cost at call  130 :  271.8379 
+#> Model cost at call  133 :  270.064 
+#> Model cost at call  135 :  270.064 
+#> Model cost at call  138 :  268.0107 
+#> Model cost at call  140 :  268.0107 
+#> Model cost at call  144 :  265.6194 
+#> Model cost at call  146 :  265.6194 
+#> Model cost at call  148 :  265.6194 
+#> Model cost at call  149 :  263.4825 
+#> Model cost at call  151 :  263.4825 
+#> Model cost at call  153 :  263.4824 
+#> Model cost at call  154 :  262.0988 
+#> Model cost at call  156 :  262.0988 
+#> Model cost at call  160 :  260.7078 
+#> Model cost at call  162 :  260.7078 
+#> Model cost at call  165 :  259.9453 
+#> Model cost at call  167 :  259.9453 
+#> Model cost at call  170 :  258.9623 
+#> Model cost at call  172 :  258.9623 
+#> Model cost at call  174 :  258.962 
+#> Model cost at call  176 :  258.0119 
+#> Model cost at call  178 :  258.0119 
+#> Model cost at call  180 :  258.0119 
+#> Model cost at call  181 :  257.8698 
+#> Model cost at call  183 :  257.8698 
+#> Model cost at call  186 :  256.8608 
+#> Model cost at call  188 :  256.8608 
+#> Model cost at call  190 :  256.8608 
+#> Model cost at call  191 :  256.2306 
+#> Model cost at call  193 :  256.2306 
+#> Model cost at call  195 :  256.2305 
+#> Model cost at call  196 :  255.7119 
+#> Model cost at call  198 :  255.7118 
+#> Model cost at call  201 :  255.3323 
+#> Model cost at call  203 :  255.3323 
+#> Model cost at call  205 :  255.3323 
+#> Model cost at call  206 :  254.6653 
+#> Model cost at call  208 :  254.6653 
+#> Model cost at call  211 :  254.3984 
+#> Model cost at call  213 :  254.3984 
+#> Model cost at call  216 :  253.3199 
+#> Model cost at call  218 :  253.3199 
+#> Model cost at call  220 :  253.3198 
+#> Model cost at call  221 :  252.4845 
+#> Model cost at call  223 :  252.4845 
+#> Model cost at call  225 :  252.4845 
+#> Model cost at call  226 :  251.6917 
+#> Model cost at call  229 :  251.6917 
+#> Model cost at call  230 :  251.6917 
+#> Model cost at call  233 :  251.0189 
+#> Model cost at call  235 :  251.0189 
+#> Model cost at call  238 :  250.6912 
+#> Model cost at call  240 :  250.6912 
+#> Model cost at call  243 :  250.5546 
+#> Model cost at call  245 :  250.5546 
+#> Model cost at call  248 :  250.466 
+#> Model cost at call  249 :  250.3744 
+#> Model cost at call  250 :  249.9681 
+#> Model cost at call  251 :  249.2215 
+#> Model cost at call  260 :  248.919 
+#> Model cost at call  264 :  248.919 
+#> Model cost at call  265 :  248.8876 
+#> Model cost at call  267 :  248.8876 
+#> Model cost at call  270 :  248.8521 
+#> Model cost at call  271 :  248.8178 
+#> Model cost at call  272 :  248.6837 
+#> Model cost at call  273 :  248.5989 
+#> Model cost at call  276 :  248.5989 
+#> Model cost at call  278 :  248.5935 
+#> Model cost at call  280 :  248.5935 
+#> Model cost at call  282 :  248.5935 
+#> Model cost at call  283 :  248.5902 
+#> Model cost at call  284 :  248.5902 
+#> Model cost at call  289 :  248.5902 
+#> Model cost at call  298 :  248.5902 
+#> Model cost at call  309 :  248.5902 
+#> Model cost at call  311 :  248.5902 
+#> Optimisation by method Port successfully terminated.
summary(f.w.man)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:53 2016 
+#> Date of summary: Fri Nov 18 15:19:53 2016 
+#> 
+#> 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 316 model solutions performed in 1.337 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 -0.09455        -0.3351
+#> log_k_parent    0.53123       1.0000 -0.17800        -0.3360
+#> log_k_m1       -0.09455      -0.1780  1.00000         0.7616
+#> f_parent_ilr_1 -0.33513      -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 2.222e-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 99.485977  -0.025977   1
+#>     0   parent   102.04 99.485977   2.554023   1
+#>     1   parent    93.50 90.186118   3.313882   1
+#>     1   parent    92.50 90.186118   2.313882   1
+#>     3   parent    63.23 74.113162 -10.883162   1
+#>     3   parent    68.99 74.113162  -5.123162   1
+#>     7   parent    52.32 50.050295   2.269705   1
+#>     7   parent    55.13 50.050295   5.079705   1
+#>    14   parent    27.27 25.179750   2.090250   1
+#>    14   parent    26.64 25.179750   1.460250   1
+#>    21   parent    11.50 12.667654  -1.167654   1
+#>    21   parent    11.64 12.667654  -1.027654   1
+#>    35   parent     2.85  3.206164  -0.356164   1
+#>    35   parent     2.91  3.206164  -0.296164   1
+#>    50   parent     0.69  0.735619  -0.045619   1
+#>    50   parent     0.63  0.735619  -0.105619   1
+#>    75   parent     0.05  0.063256  -0.013256   1
+#>    75   parent     0.06  0.063256  -0.003256   1
+#>   100   parent       NA  0.005439         NA   1
+#>   100   parent       NA  0.005439         NA   1
+#>   120   parent       NA  0.000764         NA   1
+#>   120   parent       NA  0.000764         NA   1
+#>     0       m1     0.00  0.000000   0.000000   2
+#>     0       m1     0.00  0.000000   0.000000   2
+#>     1       m1     4.84  4.787287   0.052713   2
+#>     1       m1     5.64  4.787287   0.852713   2
+#>     3       m1    12.91 12.987848  -0.077848   2
+#>     3       m1    12.96 12.987848  -0.027848   2
+#>     7       m1    22.97 24.996945  -2.026945   2
+#>     7       m1    24.47 24.996945  -0.526945   2
+#>    14       m1    41.69 36.663527   5.026473   2
+#>    14       m1    33.21 36.663527  -3.453527   2
+#>    21       m1    44.37 41.656812   2.713188   2
+#>    21       m1    46.44 41.656812   4.783188   2
+#>    35       m1    41.22 43.350311  -2.130311   2
+#>    35       m1    37.95 43.350311  -5.400311   2
+#>    50       m1    41.19 41.256364  -0.066364   2
+#>    50       m1    40.01 41.256364  -1.246364   2
+#>    75       m1    40.09 36.460566   3.629434   2
+#>    75       m1    33.85 36.460566  -2.610566   2
+#>   100       m1    31.04 31.969288  -0.929288   2
+#>   100       m1    33.13 31.969288   1.160712   2
+#>   120       m1    25.15 28.760615  -3.610615   2
+#>   120       m1    33.31 28.760615   4.549385   2
f.w.man.irls <- mkinfit(SFO_SFO.ff, dw, err = "err.man",
+                       reweight.method = "obs")
#> Model cost at call  1 :  3949.676 
+#> Model cost at call  2 :  3949.676 
+#> Model cost at call  5 :  3949.676 
+#> Model cost at call  6 :  2252.859 
+#> Model cost at call  8 :  2252.858 
+#> Model cost at call  9 :  2252.826 
+#> Model cost at call  13 :  1567.343 
+#> Model cost at call  14 :  1567.342 
+#> Model cost at call  15 :  1567.333 
+#> Model cost at call  18 :  1041.524 
+#> Model cost at call  19 :  1041.522 
+#> Model cost at call  24 :  840.4649 
+#> Model cost at call  26 :  840.4646 
+#> Model cost at call  29 :  782.303 
+#> Model cost at call  31 :  782.3028 
+#> Model cost at call  34 :  664.539 
+#> Model cost at call  36 :  664.5389 
+#> Model cost at call  40 :  615.7908 
+#> Model cost at call  42 :  615.7907 
+#> Model cost at call  45 :  569.5971 
+#> Model cost at call  47 :  569.597 
+#> Model cost at call  50 :  517.3175 
+#> Model cost at call  52 :  517.3173 
+#> Model cost at call  56 :  464.8158 
+#> Model cost at call  58 :  464.8157 
+#> Model cost at call  62 :  433.0031 
+#> Model cost at call  64 :  433.003 
+#> Model cost at call  67 :  423.7407 
+#> Model cost at call  69 :  423.7406 
+#> Model cost at call  70 :  423.7392 
+#> Model cost at call  72 :  346.2781 
+#> Model cost at call  74 :  346.278 
+#> Model cost at call  75 :  346.2779 
+#> Model cost at call  78 :  334.5399 
+#> Model cost at call  80 :  334.5398 
+#> Model cost at call  83 :  324.139 
+#> Model cost at call  85 :  324.1389 
+#> Model cost at call  88 :  319.7514 
+#> Model cost at call  90 :  319.7514 
+#> Model cost at call  94 :  300.9426 
+#> Model cost at call  96 :  300.9425 
+#> Model cost at call  100 :  295.8803 
+#> Model cost at call  102 :  295.8803 
+#> Model cost at call  105 :  290.3288 
+#> Model cost at call  107 :  290.3287 
+#> Model cost at call  111 :  284.3257 
+#> Model cost at call  113 :  284.3257 
+#> Model cost at call  116 :  282.3972 
+#> Model cost at call  118 :  282.3972 
+#> Model cost at call  122 :  273.7385 
+#> Model cost at call  124 :  273.7385 
+#> Model cost at call  128 :  271.8379 
+#> Model cost at call  130 :  271.8379 
+#> Model cost at call  133 :  270.064 
+#> Model cost at call  135 :  270.064 
+#> Model cost at call  138 :  268.0107 
+#> Model cost at call  140 :  268.0107 
+#> Model cost at call  144 :  265.6194 
+#> Model cost at call  146 :  265.6194 
+#> Model cost at call  148 :  265.6194 
+#> Model cost at call  149 :  263.4825 
+#> Model cost at call  151 :  263.4825 
+#> Model cost at call  153 :  263.4824 
+#> Model cost at call  154 :  262.0988 
+#> Model cost at call  156 :  262.0988 
+#> Model cost at call  160 :  260.7078 
+#> Model cost at call  162 :  260.7078 
+#> Model cost at call  165 :  259.9453 
+#> Model cost at call  167 :  259.9453 
+#> Model cost at call  170 :  258.9623 
+#> Model cost at call  172 :  258.9623 
+#> Model cost at call  174 :  258.962 
+#> Model cost at call  176 :  258.0119 
+#> Model cost at call  178 :  258.0119 
+#> Model cost at call  180 :  258.0119 
+#> Model cost at call  181 :  257.8698 
+#> Model cost at call  183 :  257.8698 
+#> Model cost at call  186 :  256.8608 
+#> Model cost at call  188 :  256.8608 
+#> Model cost at call  190 :  256.8608 
+#> Model cost at call  191 :  256.2306 
+#> Model cost at call  193 :  256.2306 
+#> Model cost at call  195 :  256.2305 
+#> Model cost at call  196 :  255.7119 
+#> Model cost at call  198 :  255.7118 
+#> Model cost at call  201 :  255.3323 
+#> Model cost at call  203 :  255.3323 
+#> Model cost at call  205 :  255.3323 
+#> Model cost at call  206 :  254.6653 
+#> Model cost at call  208 :  254.6653 
+#> Model cost at call  211 :  254.3984 
+#> Model cost at call  213 :  254.3984 
+#> Model cost at call  216 :  253.3199 
+#> Model cost at call  218 :  253.3199 
+#> Model cost at call  220 :  253.3198 
+#> Model cost at call  221 :  252.4845 
+#> Model cost at call  223 :  252.4845 
+#> Model cost at call  225 :  252.4845 
+#> Model cost at call  226 :  251.6917 
+#> Model cost at call  229 :  251.6917 
+#> Model cost at call  230 :  251.6917 
+#> Model cost at call  233 :  251.0189 
+#> Model cost at call  235 :  251.0189 
+#> Model cost at call  238 :  250.6912 
+#> Model cost at call  240 :  250.6912 
+#> Model cost at call  243 :  250.5546 
+#> Model cost at call  245 :  250.5546 
+#> Model cost at call  248 :  250.466 
+#> Model cost at call  249 :  250.3744 
+#> Model cost at call  250 :  249.9681 
+#> Model cost at call  251 :  249.2215 
+#> Model cost at call  260 :  248.919 
+#> Model cost at call  264 :  248.919 
+#> Model cost at call  265 :  248.8876 
+#> Model cost at call  267 :  248.8876 
+#> Model cost at call  270 :  248.8521 
+#> Model cost at call  271 :  248.8178 
+#> Model cost at call  272 :  248.6837 
+#> Model cost at call  273 :  248.5989 
+#> Model cost at call  276 :  248.5989 
+#> Model cost at call  278 :  248.5935 
+#> Model cost at call  280 :  248.5935 
+#> Model cost at call  282 :  248.5935 
+#> Model cost at call  283 :  248.5902 
+#> Model cost at call  284 :  248.5902 
+#> Model cost at call  289 :  248.5902 
+#> Model cost at call  298 :  248.5902 
+#> Model cost at call  309 :  248.5902 
+#> Model cost at call  311 :  248.5902 
+#> IRLS based on variance estimates for each observed variable
+#> Initial variance estimates are:
+#>    parent        m1 
+#> 11.536305  7.443046 
+#> Model cost at call  317 :  40 
+#> Model cost at call  319 :  40 
+#> Model cost at call  324 :  39.98891 
+#> Model cost at call  325 :  39.9889 
+#> Model cost at call  327 :  39.98886 
+#> Model cost at call  331 :  39.98871 
+#> Model cost at call  333 :  39.97254 
+#> Model cost at call  336 :  39.97253 
+#> Model cost at call  338 :  39.96929 
+#> Model cost at call  340 :  39.96929 
+#> Model cost at call  344 :  39.96849 
+#> Model cost at call  346 :  39.96849 
+#> Model cost at call  348 :  39.96849 
+#> Model cost at call  349 :  39.96774 
+#> Model cost at call  351 :  39.96774 
+#> Model cost at call  353 :  39.96774 
+#> Model cost at call  354 :  39.96714 
+#> Model cost at call  356 :  39.96714 
+#> Model cost at call  359 :  39.96617 
+#> Model cost at call  361 :  39.96617 
+#> Model cost at call  364 :  39.96606 
+#> Model cost at call  366 :  39.96606 
+#> Model cost at call  369 :  39.96551 
+#> Model cost at call  371 :  39.96551 
+#> Model cost at call  372 :  39.96551 
+#> Model cost at call  375 :  39.96527 
+#> Model cost at call  378 :  39.96527 
+#> Model cost at call  379 :  39.96527 
+#> Model cost at call  380 :  39.96525 
+#> Model cost at call  382 :  39.96525 
+#> Model cost at call  385 :  39.9651 
+#> Model cost at call  387 :  39.9651 
+#> Model cost at call  388 :  39.9651 
+#> Model cost at call  390 :  39.96502 
+#> Model cost at call  393 :  39.96502 
+#> Model cost at call  396 :  39.96502 
+#> Model cost at call  397 :  39.96467 
+#> Model cost at call  398 :  39.96422 
+#> Model cost at call  399 :  39.9624 
+#> Model cost at call  400 :  39.95909 
+#> Model cost at call  402 :  39.95909 
+#> Model cost at call  405 :  39.9571 
+#> Model cost at call  407 :  39.95709 
+#> Model cost at call  413 :  39.95479 
+#> Model cost at call  414 :  39.95479 
+#> Model cost at call  415 :  39.95479 
+#> Model cost at call  417 :  39.95479 
+#> Model cost at call  419 :  39.95398 
+#> Model cost at call  422 :  39.95398 
+#> Model cost at call  424 :  39.95387 
+#> Model cost at call  429 :  39.95384 
+#> Model cost at call  432 :  39.95384 
+#> Model cost at call  435 :  39.95384 
+#> Model cost at call  437 :  39.95384 
+#> Model cost at call  438 :  39.95384 
+#> Model cost at call  446 :  39.95384 
+#> Model cost at call  455 :  39.95384 
+#> Model cost at call  469 :  39.95384 
+#> Model cost at call  473 :  39.95384 
+#> Iteration 1 yields variance estimates:
+#>    parent        m1 
+#> 11.572891  7.408116 
+#> Sum of squared differences to last variance estimates: 7e-05 
+#> Iteration 2 yields variance estimates:
+#>    parent        m1 
+#> 11.573402  7.407847 
+#> Sum of squared differences to last variance estimates: 8.1e-09 
+#> Optimisation by method Port successfully terminated.
summary(f.w.man.irls)
#> mkin version:    0.9.44.9000 
+#> R version:       3.3.2 
+#> Date of fit:     Fri Nov 18 15:19:55 2016 
+#> Date of summary: Fri Nov 18 15:19:55 2016 
+#> 
+#> 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 648 model solutions performed in 2.716 s
+#> 
+#> Weighting: manual then iterative reweighting method obs
+#> 
+#> 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        -0.6147
+#> 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  -0.6147      -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 8.178e-37 96.040000 1.033e+02
+#> k_parent        0.09906  21.930 1.015e-22  0.090310 1.087e-01
+#> k_m1            0.00524   7.996 8.488e-10  0.004066 6.753e-03
+#> f_parent_to_m1  0.51340  23.000 2.038e-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     132.281 439.43
+#> 
+#> Data:
+#>  time variable observed predicted   residual err.ini   err
+#>     0   parent    99.46 9.967e+01 -2.122e-01       1 3.402
+#>     0   parent   102.04 9.967e+01  2.368e+00       1 3.402
+#>     1   parent    93.50 9.027e+01  3.228e+00       1 3.402
+#>     1   parent    92.50 9.027e+01  2.228e+00       1 3.402
+#>     3   parent    63.23 7.405e+01 -1.082e+01       1 3.402
+#>     3   parent    68.99 7.405e+01 -5.056e+00       1 3.402
+#>     7   parent    52.32 4.982e+01  2.499e+00       1 3.402
+#>     7   parent    55.13 4.982e+01  5.309e+00       1 3.402
+#>    14   parent    27.27 2.490e+01  2.367e+00       1 3.402
+#>    14   parent    26.64 2.490e+01  1.737e+00       1 3.402
+#>    21   parent    11.50 1.245e+01 -9.477e-01       1 3.402
+#>    21   parent    11.64 1.245e+01 -8.077e-01       1 3.402
+#>    35   parent     2.85 3.110e+00 -2.600e-01       1 3.402
+#>    35   parent     2.91 3.110e+00 -2.000e-01       1 3.402
+#>    50   parent     0.69 7.037e-01 -1.375e-02       1 3.402
+#>    50   parent     0.63 7.037e-01 -7.375e-02       1 3.402
+#>    75   parent     0.05 5.913e-02 -9.134e-03       1 3.402
+#>    75   parent     0.06 5.913e-02  8.659e-04       1 3.402
+#>   100   parent       NA 4.969e-03         NA       1 3.402
+#>   100   parent       NA 4.969e-03         NA       1 3.402
+#>   120   parent       NA 6.852e-04         NA       1 3.402
+#>   120   parent       NA 6.852e-04         NA       1 3.402
+#>     0       m1     0.00 0.000e+00  0.000e+00       2 2.722
+#>     0       m1     0.00 0.000e+00  0.000e+00       2 2.722
+#>     1       m1     4.84 4.813e+00  2.672e-02       2 2.722
+#>     1       m1     5.64 4.813e+00  8.267e-01       2 2.722
+#>     3       m1    12.91 1.305e+01 -1.378e-01       2 2.722
+#>     3       m1    12.96 1.305e+01 -8.778e-02       2 2.722
+#>     7       m1    22.97 2.508e+01 -2.106e+00       2 2.722
+#>     7       m1    24.47 2.508e+01 -6.061e-01       2 2.722
+#>    14       m1    41.69 3.671e+01  4.983e+00       2 2.722
+#>    14       m1    33.21 3.671e+01 -3.497e+00       2 2.722
+#>    21       m1    44.37 4.165e+01  2.719e+00       2 2.722
+#>    21       m1    46.44 4.165e+01  4.789e+00       2 2.722
+#>    35       m1    41.22 4.329e+01 -2.069e+00       2 2.722
+#>    35       m1    37.95 4.329e+01 -5.339e+00       2 2.722
+#>    50       m1    41.19 4.119e+01 -3.394e-03       2 2.722
+#>    50       m1    40.01 4.119e+01 -1.183e+00       2 2.722
+#>    75       m1    40.09 3.644e+01  3.652e+00       2 2.722
+#>    75       m1    33.85 3.644e+01 -2.588e+00       2 2.722
+#>   100       m1    31.04 3.199e+01 -9.497e-01       2 2.722
+#>   100       m1    33.13 3.199e+01  1.140e+00       2 2.722
+#>   120       m1    25.15 2.881e+01 -3.659e+00       2 2.722
+#>   120       m1    33.31 2.881e+01  4.501e+00       2 2.722

+

   
   
#> 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)
-## ---------------------------------------------

+
+# 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"))
#> Successfully compiled differential equation model from auto-generated C code.

+# Show details of creating the C function
+SFO_SFO <- mkinmod(
+  parent = mkinsub("SFO", "m1"),
+  m1 = mkinsub("SFO"), verbose = TRUE)
#> Compilation argument:
+#>  /usr/lib/R/bin/R CMD SHLIB file21efdcf882f.c 2> file21efdcf882f.c.err.txt 
+#> Program source:
+#>   1: #include <R.h>
+#>   2: 
+#>   3: 
+#>   4: static double parms [3];
+#>   5: #define k_parent_sink parms[0]
+#>   6: #define k_parent_m1 parms[1]
+#>   7: #define k_m1_sink parms[2]
+#>   8: 
+#>   9: void initpar(void (* odeparms)(int *, double *)) {
+#>  10:     int N = 3;
+#>  11:     odeparms(&N, parms);
+#>  12: }
+#>  13: 
+#>  14: 
+#>  15: void func ( int * n, double * t, double * y, double * f, double * rpar, int * ipar ) {
+#>  16: 
+#>  17: f[0] = - k_parent_sink * y[0] - k_parent_m1 * y[0];
+#>  18: f[1] = + k_parent_m1 * y[0] - k_m1_sink * y[1];
+#>  19: }
#> Successfully compiled differential equation model from auto-generated C code.

+# 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)

   
   
#>     time   parent       m1
 #> 201   20 4.978707 27.46227
#>    user  system elapsed 
-#>   0.024   0.004   0.004 
  system.time(
+#>   0.008   0.024   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   0.003 
  system.time(
+#>   0.020   0.000   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 
-#>   0.032   0.000   0.035
+#> 0.032 0.000 0.034
#> Successfully compiled differential equation model from auto-generated C code.
## Not run: mkinfit(model, data, plot=TRUE)
+ A2 = list(type = "SFO"), use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
mkinfit(model, data)
#> Model cost at call 1 : 2511.655 +#> Model cost at call 2 : 2511.655 +#> Model cost at call 11 : 1436.639 +#> Model cost at call 12 : 1436.638 +#> Model cost at call 13 : 1436.566 +#> Model cost at call 21 : 643.6583 +#> Model cost at call 22 : 643.6583 +#> Model cost at call 23 : 643.6582 +#> Model cost at call 29 : 643.6576 +#> Model cost at call 31 : 454.0244 +#> Model cost at call 32 : 454.0241 +#> Model cost at call 34 : 454.0229 +#> Model cost at call 43 : 378.1144 +#> Model cost at call 45 : 378.1143 +#> Model cost at call 53 : 357.245 +#> Model cost at call 55 : 357.2449 +#> Model cost at call 56 : 357.2447 +#> Model cost at call 63 : 354.3415 +#> Model cost at call 64 : 354.3415 +#> Model cost at call 65 : 354.3413 +#> Model cost at call 73 : 332.49 +#> Model cost at call 74 : 332.49 +#> Model cost at call 81 : 332.4899 +#> Model cost at call 83 : 315.2962 +#> Model cost at call 84 : 306.3085 +#> Model cost at call 86 : 306.3084 +#> Model cost at call 87 : 306.3084 +#> Model cost at call 92 : 306.3083 +#> Model cost at call 94 : 290.6377 +#> Model cost at call 96 : 290.6375 +#> Model cost at call 98 : 290.6375 +#> Model cost at call 101 : 290.6371 +#> Model cost at call 105 : 269.09 +#> Model cost at call 107 : 269.0899 +#> Model cost at call 115 : 259.7551 +#> Model cost at call 120 : 259.7549 +#> Model cost at call 123 : 259.7547 +#> Model cost at call 126 : 253.7973 +#> Model cost at call 128 : 253.7972 +#> Model cost at call 137 : 251.7358 +#> Model cost at call 139 : 251.7358 +#> Model cost at call 147 : 250.7394 +#> Model cost at call 149 : 250.7393 +#> Model cost at call 157 : 249.1148 +#> Model cost at call 159 : 249.1148 +#> Model cost at call 167 : 246.8768 +#> Model cost at call 169 : 246.8768 +#> Model cost at call 177 : 244.9758 +#> Model cost at call 179 : 244.9758 +#> Model cost at call 187 : 243.2914 +#> Model cost at call 189 : 243.2914 +#> Model cost at call 190 : 243.2914 +#> Model cost at call 194 : 243.2914 +#> Model cost at call 199 : 242.9202 +#> Model cost at call 201 : 242.9202 +#> Model cost at call 202 : 242.9202 +#> Model cost at call 209 : 242.7695 +#> Model cost at call 211 : 242.7695 +#> Model cost at call 216 : 242.7695 +#> Model cost at call 219 : 242.5771 +#> Model cost at call 221 : 242.5771 +#> Model cost at call 229 : 242.4402 +#> Model cost at call 231 : 242.4402 +#> Model cost at call 239 : 242.1878 +#> Model cost at call 241 : 242.1878 +#> Model cost at call 249 : 242.0553 +#> Model cost at call 251 : 242.0553 +#> Model cost at call 256 : 242.0553 +#> Model cost at call 259 : 241.8761 +#> Model cost at call 260 : 241.7412 +#> Model cost at call 261 : 241.6954 +#> Model cost at call 264 : 241.6954 +#> Model cost at call 275 : 241.5982 +#> Model cost at call 277 : 241.5982 +#> Model cost at call 285 : 241.5459 +#> Model cost at call 287 : 241.5459 +#> Model cost at call 295 : 241.4837 +#> Model cost at call 297 : 241.4837 +#> Model cost at call 305 : 241.3882 +#> Model cost at call 306 : 241.3161 +#> Model cost at call 307 : 241.2315 +#> Model cost at call 309 : 241.2315 +#> Model cost at call 314 : 241.2315 +#> Model cost at call 317 : 240.9738 +#> Model cost at call 322 : 240.9738 +#> Model cost at call 327 : 240.8244 +#> Model cost at call 329 : 240.8244 +#> Model cost at call 337 : 240.7005 +#> Model cost at call 339 : 240.7005 +#> Model cost at call 342 : 240.7005 +#> Model cost at call 347 : 240.629 +#> Model cost at call 350 : 240.629 +#> Model cost at call 357 : 240.6193 +#> Model cost at call 358 : 240.6193 +#> Model cost at call 364 : 240.6193 +#> Model cost at call 367 : 240.6193 +#> Model cost at call 369 : 240.5873 +#> Model cost at call 374 : 240.5873 +#> Model cost at call 380 : 240.578 +#> Model cost at call 382 : 240.578 +#> Model cost at call 390 : 240.5723 +#> Model cost at call 393 : 240.5723 +#> Model cost at call 403 : 240.569 +#> Model cost at call 404 : 240.569 +#> Model cost at call 413 : 240.569 +#> Model cost at call 415 : 240.5688 +#> Model cost at call 416 : 240.5688 +#> Model cost at call 417 : 240.5688 +#> Model cost at call 431 : 240.5686 +#> Model cost at call 432 : 240.5686 +#> Model cost at call 434 : 240.5686 +#> Model cost at call 443 : 240.5686 +#> Model cost at call 444 : 240.5686 +#> Model cost at call 447 : 240.5686 +#> Model cost at call 449 : 240.5686 +#> Model cost at call 450 : 240.5686 +#> Model cost at call 466 : 240.5686 +#> Model cost at call 470 : 240.5686 +#> Model cost at call 485 : 240.5686 +#> Model cost at call 509 : 240.5686 +#> Optimisation by method Port successfully terminated.
#> $par +#> parent_0 log_k_parent log_k_A1 log_k_B1 log_k_C1 +#> 91.9181598 -3.0020485 -4.2735924 -3.9846764 -2.7852180 +#> log_k_A2 f_parent_ilr_1 f_parent_ilr_2 f_A1_ilr_1 +#> -3.7166415 0.4718588 -0.3589948 -0.1477244 +#> +#> $ssr +#> [1] 240.5686 +#> +#> $convergence +#> [1] 0 +#> +#> $iterations +#> [1] 43 +#> +#> $evaluations +#> function gradient +#> 62 441 +#> +#> $counts +#> [1] "relative convergence (4)" +#> +#> $hessian +#> parent_0 log_k_parent log_k_A1 log_k_B1 +#> parent_0 7.3650812 -92.141920 -1.001134e+01 -2.432415e+00 +#> log_k_parent -92.1419204 6632.673492 -4.316240e+01 -1.320833e+01 +#> log_k_A1 -10.0113364 -43.162398 6.071628e+02 0.000000e+00 +#> log_k_B1 -2.4324147 -13.208329 0.000000e+00 1.572303e+02 +#> log_k_C1 -4.7153201 -118.288037 -5.878291e-05 -3.073041e-06 +#> log_k_A2 -0.4360727 -5.304259 -1.977980e+01 0.000000e+00 +#> f_parent_ilr_1 10.5460899 271.145438 -5.299954e+02 1.874235e+02 +#> f_parent_ilr_2 11.6409409 222.570696 -4.773816e+02 -1.159875e+02 +#> f_A1_ilr_1 0.5572072 10.374810 2.850173e+01 0.000000e+00 +#> log_k_C1 log_k_A2 f_parent_ilr_1 f_parent_ilr_2 +#> parent_0 -4.715320e+00 -4.360727e-01 10.54609 11.64094 +#> log_k_parent -1.182880e+02 -5.304259e+00 271.14544 222.57070 +#> log_k_A1 -5.878291e-05 -1.977980e+01 -529.99537 -477.38164 +#> log_k_B1 -3.073041e-06 0.000000e+00 187.42348 -115.98754 +#> log_k_C1 3.372749e+02 -2.395674e-06 56.85184 305.98862 +#> log_k_A2 -2.395674e-06 2.749192e+01 -23.08549 -20.79373 +#> f_parent_ilr_1 5.685184e+01 -2.308549e+01 1256.24941 632.09769 +#> f_parent_ilr_2 3.059886e+02 -2.079373e+01 632.09769 1250.65147 +#> f_A1_ilr_1 3.158891e-06 -3.129286e+01 29.49830 26.56991 +#> f_A1_ilr_1 +#> parent_0 5.572072e-01 +#> log_k_parent 1.037481e+01 +#> log_k_A1 2.850173e+01 +#> log_k_B1 0.000000e+00 +#> log_k_C1 3.158891e-06 +#> log_k_A2 -3.129286e+01 +#> f_parent_ilr_1 2.949830e+01 +#> f_parent_ilr_2 2.656991e+01 +#> f_A1_ilr_1 3.998554e+01 +#> +#> $residuals +#> parent parent parent parent parent parent parent +#> -1.2818402 -1.9372115 -0.5105519 3.8165318 -2.3531716 4.8043342 -2.2775432 +#> parent A1 A1 A1 A1 A1 A1 +#> -5.3608524 4.1967522 2.9032987 -1.3124875 -0.6021093 2.5092324 -1.8861396 +#> B1 B1 B1 B1 B1 C1 C1 +#> 4.3801768 5.5002481 -5.7917184 1.3852658 0.5313301 1.2796458 1.7105311 +#> C1 C1 C1 C1 C1 A2 A2 +#> 3.7116712 -0.1182953 0.5228429 -0.8570298 -3.5476556 -0.5447276 -1.3652404 +#> A2 A2 A2 A2 A2 +#> -0.3330261 -0.5802059 0.1285850 0.2119280 -0.1381990 +#> +#> $ms +#> [1] 7.289956 +#> +#> $var_ms +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $var_ms_unscaled +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $var_ms_unweighted +#> parent A1 B1 C1 A2 +#> 10.3459333 6.3301336 17.0367907 4.5639474 0.3841002 +#> +#> $rank +#> [1] 9 +#> +#> $df.residual +#> [1] 24 +#> +#> $solution_type +#> [1] "deSolve" +#> +#> $transform_rates +#> [1] TRUE +#> +#> $transform_fractions +#> [1] TRUE +#> +#> $method.modFit +#> [1] "Port" +#> +#> $maxit.modFit +#> [1] "auto" +#> +#> $calls +#> [1] 523 +#> +#> $time +#> user system elapsed +#> 5.004 0.000 5.004 +#> +#> $mkinmod +#> <mkinmod> model generated with +#> Use of formation fractions $use_of_ff: max +#> Specification $spec: +#> $parent +#> $type: SFO; $to: A1, B1, C1; $sink: FALSE +#> $A1 +#> $type: SFO; $to: A2; $sink: TRUE +#> $B1 +#> $type: SFO; $sink: TRUE +#> $C1 +#> $type: SFO; $sink: TRUE +#> $A2 +#> $type: SFO; $sink: TRUE +#> Coefficient matrix $coefmat available +#> Compiled model $cf available +#> +#> $observed +#> name time value +#> 1 parent 0 93.20 +#> 2 parent 1 89.40 +#> 3 parent 3 79.70 +#> 4 parent 7 61.10 +#> 5 parent 14 48.20 +#> 6 parent 30 15.90 +#> 7 parent 62 6.50 +#> 8 parent 100 6.00 +#> 9 A1 0 NA +#> 10 A1 1 NA +#> 11 A1 3 0.55 +#> 12 A1 7 6.87 +#> 13 A1 14 17.08 +#> 14 A1 30 21.68 +#> 15 A1 62 15.77 +#> 16 A1 100 13.63 +#> 17 B1 0 NA +#> 18 B1 1 NA +#> 19 B1 3 NA +#> 20 B1 7 0.55 +#> 21 B1 14 2.31 +#> 22 B1 30 15.76 +#> 23 B1 62 6.36 +#> 24 B1 100 3.74 +#> 25 C1 0 NA +#> 26 C1 1 0.55 +#> 27 C1 3 3.20 +#> 28 C1 7 5.46 +#> 29 C1 14 12.55 +#> 30 C1 30 10.45 +#> 31 C1 62 4.74 +#> 32 C1 100 4.33 +#> 33 A2 0 NA +#> 34 A2 1 0.55 +#> 35 A2 3 1.41 +#> 36 A2 7 0.55 +#> 37 A2 14 1.29 +#> 38 A2 30 1.95 +#> 39 A2 62 3.54 +#> 40 A2 100 3.86 +#> +#> $obs_vars +#> [1] "parent" "A1" "B1" "C1" "A2" +#> +#> $predicted +#> name time value +#> 1 parent 0.000000 91.918159794 +#> 2 parent 1.000000 87.462788491 +#> 3 parent 1.010101 87.418904506 +#> 4 parent 2.020202 83.139880984 +#> 5 parent 3.000000 79.189448055 +#> 6 parent 3.030303 79.070309209 +#> 7 parent 4.040404 75.199936833 +#> 8 parent 5.050505 71.519013349 +#> 9 parent 6.060606 68.018265517 +#> 10 parent 7.000000 64.916531757 +#> 11 parent 7.070707 64.688874011 +#> 12 parent 8.080808 61.522451197 +#> 13 parent 9.090909 58.511020005 +#> 14 parent 10.101010 55.646993828 +#> 15 parent 11.111111 52.923157412 +#> 16 parent 12.121212 50.332648680 +#> 17 parent 13.131313 47.868941444 +#> 18 parent 14.000000 45.846828365 +#> 19 parent 14.141414 45.525828960 +#> 20 parent 15.151515 43.297408299 +#> 21 parent 16.161616 41.178065468 +#> 22 parent 17.171717 39.162461272 +#> 23 parent 18.181818 37.245517861 +#> 24 parent 19.191919 35.422405939 +#> 25 parent 20.202020 33.688532595 +#> 26 parent 21.212121 32.039529737 +#> 27 parent 22.222222 30.471243081 +#> 28 parent 23.232323 28.979721692 +#> 29 parent 24.242424 27.561208025 +#> 30 parent 25.252525 26.212128463 +#> 31 parent 26.262626 24.929084310 +#> 32 parent 27.272727 23.708843233 +#> 33 parent 28.282828 22.548331117 +#> 34 parent 29.292929 21.444624318 +#> 35 parent 30.000000 20.704334210 +#> 36 parent 30.303030 20.394942302 +#> 37 parent 31.313131 19.396640638 +#> 38 parent 32.323232 18.447204335 +#> 39 parent 33.333333 17.544241506 +#> 40 parent 34.343434 16.685477346 +#> 41 parent 35.353535 15.868748397 +#> 42 parent 36.363636 15.091997098 +#> 43 parent 37.373737 14.353266603 +#> 44 parent 38.383838 13.650695852 +#> 45 parent 39.393939 12.982514879 +#> 46 parent 40.404040 12.347040357 +#> 47 parent 41.414141 11.742671354 +#> 48 parent 42.424242 11.167885303 +#> 49 parent 43.434343 10.621234162 +#> 50 parent 44.444444 10.101340770 +#> 51 parent 45.454545 9.606895375 +#> 52 parent 46.464646 9.136652336 +#> 53 parent 47.474747 8.689426985 +#> 54 parent 48.484848 8.264092640 +#> 55 parent 49.494949 7.859577770 +#> 56 parent 50.505051 7.474863293 +#> 57 parent 51.515152 7.108980009 +#> 58 parent 52.525253 6.761006160 +#> 59 parent 53.535354 6.430065106 +#> 60 parent 54.545455 6.115323117 +#> 61 parent 55.555556 5.815987274 +#> 62 parent 56.565657 5.531303470 +#> 63 parent 57.575758 5.260554508 +#> 64 parent 58.585859 5.003058299 +#> 65 parent 59.595960 4.758166141 +#> 66 parent 60.606061 4.525261085 +#> 67 parent 61.616162 4.303756381 +#> 68 parent 62.000000 4.222456793 +#> 69 parent 62.626263 4.093093997 +#> 70 parent 63.636364 3.892743220 +#> 71 parent 64.646465 3.702199310 +#> 72 parent 65.656566 3.520982238 +#> 73 parent 66.666667 3.348635468 +#> 74 parent 67.676768 3.184724813 +#> 75 parent 68.686869 3.028837337 +#> 76 parent 69.696970 2.880580317 +#> 77 parent 70.707071 2.739580256 +#> 78 parent 71.717172 2.605481934 +#> 79 parent 72.727273 2.477947523 +#> 80 parent 73.737374 2.356655730 +#> 81 parent 74.747475 2.241300986 +#> 82 parent 75.757576 2.131592683 +#> 83 parent 76.767677 2.027254437 +#> 84 parent 77.777778 1.928023390 +#> 85 parent 78.787879 1.833649553 +#> 86 parent 79.797980 1.743895173 +#> 87 parent 80.808081 1.658534134 +#> 88 parent 81.818182 1.577351390 +#> 89 parent 82.828283 1.500142419 +#> 90 parent 83.838384 1.426712710 +#> 91 parent 84.848485 1.356877275 +#> 92 parent 85.858586 1.290460179 +#> 93 parent 86.868687 1.227294099 +#> 94 parent 87.878788 1.167219904 +#> 95 parent 88.888889 1.110086250 +#> 96 parent 89.898990 1.055749203 +#> 97 parent 90.909091 1.004071872 +#> 98 parent 91.919192 0.954924068 +#> 99 parent 92.929293 0.908181975 +#> 100 parent 93.939394 0.863727837 +#> 101 parent 94.949495 0.821449662 +#> 102 parent 95.959596 0.781240940 +#> 103 parent 96.969697 0.743000375 +#> 104 parent 97.979798 0.706631627 +#> 105 parent 98.989899 0.672043075 +#> 106 parent 100.000000 0.639147580 +#> 107 A1 0.000000 0.000000000 +#> 108 A1 1.000000 1.685461006 +#> 109 A1 1.010101 1.701940789 +#> 110 A1 2.020202 3.296791533 +#> 111 A1 3.000000 4.746752202 +#> 112 A1 3.030303 4.790126465 +#> 113 A1 4.040404 6.187242320 +#> 114 A1 5.050505 7.493171988 +#> 115 A1 6.060606 8.712697491 +#> 116 A1 7.000000 9.773298725 +#> 117 A1 7.070707 9.850362326 +#> 118 A1 8.080808 10.910483202 +#> 119 A1 9.090909 11.897161206 +#> 120 A1 10.101010 12.814292412 +#> 121 A1 11.111111 13.665577981 +#> 122 A1 12.121212 14.454533757 +#> 123 A1 13.131313 15.184499397 +#> 124 A1 14.000000 15.767512526 +#> 125 A1 14.141414 15.858647054 +#> 126 A1 15.151515 16.479989628 +#> 127 A1 16.161616 17.051388624 +#> 128 A1 17.171717 17.575561608 +#> 129 A1 18.181818 18.055089316 +#> 130 A1 19.191919 18.492422399 +#> 131 A1 20.202020 18.889887843 +#> 132 A1 21.212121 19.249695079 +#> 133 A1 22.222222 19.573941783 +#> 134 A1 23.232323 19.864619397 +#> 135 A1 24.242424 20.123618383 +#> 136 A1 25.252525 20.352733211 +#> 137 A1 26.262626 20.553667106 +#> 138 A1 27.272727 20.728036563 +#> 139 A1 28.282828 20.877375640 +#> 140 A1 29.292929 21.003140039 +#> 141 A1 30.000000 21.077890710 +#> 142 A1 30.303030 21.106710984 +#> 143 A1 31.313131 21.189398917 +#> 144 A1 32.323232 21.252447002 +#> 145 A1 33.333333 21.297034466 +#> 146 A1 34.343434 21.324279770 +#> 147 A1 35.353535 21.335243623 +#> 148 A1 36.363636 21.330931858 +#> 149 A1 37.373737 21.312298151 +#> 150 A1 38.383838 21.280246621 +#> 151 A1 39.393939 21.235634295 +#> 152 A1 40.404040 21.179273450 +#> 153 A1 41.414141 21.111933845 +#> 154 A1 42.424242 21.034344838 +#> 155 A1 43.434343 20.947197407 +#> 156 A1 44.444444 20.851146060 +#> 157 A1 45.454545 20.746810660 +#> 158 A1 46.464646 20.634778158 +#> 159 A1 47.474747 20.515604239 +#> 160 A1 48.484848 20.389814887 +#> 161 A1 49.494949 20.257907875 +#> 162 A1 50.505051 20.120354180 +#> 163 A1 51.515152 19.977599327 +#> 164 A1 52.525253 19.830064674 +#> 165 A1 53.535354 19.678148618 +#> 166 A1 54.545455 19.522227762 +#> 167 A1 55.555556 19.362658007 +#> 168 A1 56.565657 19.199775600 +#> 169 A1 57.575758 19.033898126 +#> 170 A1 58.585859 18.865325451 +#> 171 A1 59.595960 18.694340625 +#> 172 A1 60.606061 18.521210729 +#> 173 A1 61.616162 18.346187688 +#> 174 A1 62.000000 18.279232408 +#> 175 A1 62.626263 18.169509043 +#> 176 A1 63.636364 17.991398686 +#> 177 A1 64.646465 17.812067549 +#> 178 A1 65.656566 17.631714275 +#> 179 A1 66.666667 17.450525840 +#> 180 A1 67.676768 17.268678156 +#> 181 A1 68.686869 17.086336636 +#> 182 A1 69.696970 16.903656738 +#> 183 A1 70.707071 16.720784474 +#> 184 A1 71.717172 16.537856901 +#> 185 A1 72.727273 16.355002582 +#> 186 A1 73.737374 16.172342031 +#> 187 A1 74.747475 15.989988127 +#> 188 A1 75.757576 15.808046514 +#> 189 A1 76.767677 15.626615980 +#> 190 A1 77.777778 15.445788814 +#> 191 A1 78.787879 15.265651148 +#> 192 A1 79.797980 15.086283284 +#> 193 A1 80.808081 14.907759996 +#> 194 A1 81.818182 14.730150830 +#> 195 A1 82.828283 14.553520376 +#> 196 A1 83.838384 14.377928535 +#> 197 A1 84.848485 14.203430771 +#> 198 A1 85.858586 14.030078345 +#> 199 A1 86.868687 13.857918547 +#> 200 A1 87.878788 13.686994907 +#> 201 A1 88.888889 13.517347398 +#> 202 A1 89.898990 13.349012635 +#> 203 A1 90.909091 13.182024056 +#> 204 A1 91.919192 13.016412097 +#> 205 A1 92.929293 12.852204356 +#> 206 A1 93.939394 12.689425755 +#> 207 A1 94.949495 12.528098688 +#> 208 A1 95.959596 12.368243159 +#> 209 A1 96.969697 12.209876925 +#> 210 A1 97.979798 12.053015616 +#> 211 A1 98.989899 11.897672861 +#> 212 A1 100.000000 11.743860400 +#> 213 B1 0.000000 0.000000000 +#> 214 B1 1.000000 0.862762059 +#> 215 B1 1.010101 0.871177048 +#> 216 B1 2.020202 1.683497848 +#> 217 B1 3.000000 2.418226457 +#> 218 B1 3.030303 2.440145075 +#> 219 B1 4.040404 3.144139999 +#> 220 B1 5.050505 3.798350490 +#> 221 B1 6.060606 4.405498633 +#> 222 B1 7.000000 4.930176837 +#> 223 B1 7.070707 4.968167964 +#> 224 B1 8.080808 5.488810347 +#> 225 B1 9.090909 5.969752521 +#> 226 B1 10.101010 6.413202316 +#> 227 B1 11.111111 6.821254568 +#> 228 B1 12.121212 7.195896744 +#> 229 B1 13.131313 7.539014282 +#> 230 B1 14.000000 7.810248132 +#> 231 B1 14.141414 7.852395679 +#> 232 B1 15.151515 8.137737320 +#> 233 B1 16.161616 8.396648072 +#> 234 B1 17.171717 8.630653651 +#> 235 B1 18.181818 8.841200774 +#> 236 B1 19.191919 9.029661109 +#> 237 B1 20.202020 9.197335022 +#> 238 B1 21.212121 9.345455150 +#> 239 B1 22.222222 9.475189788 +#> 240 B1 23.232323 9.587646116 +#> 241 B1 24.242424 9.683873262 +#> 242 B1 25.252525 9.764865214 +#> 243 B1 26.262626 9.831563593 +#> 244 B1 27.272727 9.884860284 +#> 245 B1 28.282828 9.925599936 +#> 246 B1 29.292929 9.954582344 +#> 247 B1 30.000000 9.968281596 +#> 248 B1 30.303030 9.972564708 +#> 249 B1 31.313131 9.980263783 +#> 250 B1 32.323232 9.978357919 +#> 251 B1 33.333333 9.967489009 +#> 252 B1 34.343434 9.948264327 +#> 253 B1 35.353535 9.921258285 +#> 254 B1 36.363636 9.887014102 +#> 255 B1 37.373737 9.846045383 +#> 256 B1 38.383838 9.798837632 +#> 257 B1 39.393939 9.745849674 +#> 258 B1 40.404040 9.687515023 +#> 259 B1 41.414141 9.624243169 +#> 260 B1 42.424242 9.556420809 +#> 261 B1 43.434343 9.484413012 +#> 262 B1 44.444444 9.408564328 +#> 263 B1 45.454545 9.329199843 +#> 264 B1 46.464646 9.246626179 +#> 265 B1 47.474747 9.161132446 +#> 266 B1 48.484848 9.072991146 +#> 267 B1 49.494949 8.982459028 +#> 268 B1 50.505051 8.889777910 +#> 269 B1 51.515152 8.795175451 +#> 270 B1 52.525253 8.698865886 +#> 271 B1 53.535354 8.601050726 +#> 272 B1 54.545455 8.501919425 +#> 273 B1 55.555556 8.401650008 +#> 274 B1 56.565657 8.300409672 +#> 275 B1 57.575758 8.198355355 +#> 276 B1 58.585859 8.095634277 +#> 277 B1 59.595960 7.992384454 +#> 278 B1 60.606061 7.888735183 +#> 279 B1 61.616162 7.784807509 +#> 280 B1 62.000000 7.745265792 +#> 281 B1 62.626263 7.680714664 +#> 282 B1 63.636364 7.576562482 +#> 283 B1 64.646465 7.472449799 +#> 284 B1 65.656566 7.368468826 +#> 285 B1 66.666667 7.264705509 +#> 286 B1 67.676768 7.161239868 +#> 287 B1 68.686869 7.058146319 +#> 288 B1 69.696970 6.955493978 +#> 289 B1 70.707071 6.853346953 +#> 290 B1 71.717172 6.751764620 +#> 291 B1 72.727273 6.650801882 +#> 292 B1 73.737374 6.550509419 +#> 293 B1 74.747475 6.450933922 +#> 294 B1 75.757576 6.352118318 +#> 295 B1 76.767677 6.254101979 +#> 296 B1 77.777778 6.156920928 +#> 297 B1 78.787879 6.060608023 +#> 298 B1 79.797980 5.965193142 +#> 299 B1 80.808081 5.870703355 +#> 300 B1 81.818182 5.777163083 +#> 301 B1 82.828283 5.684594257 +#> 302 B1 83.838384 5.593016458 +#> 303 B1 84.848485 5.502447062 +#> 304 B1 85.858586 5.412901366 +#> 305 B1 86.868687 5.324392718 +#> 306 B1 87.878788 5.236932630 +#> 307 B1 88.888889 5.150530889 +#> 308 B1 89.898990 5.065195670 +#> 309 B1 90.909091 4.980933628 +#> 310 B1 91.919192 4.897749999 +#> 311 B1 92.929293 4.815648688 +#> 312 B1 93.939394 4.734632351 +#> 313 B1 94.949495 4.654702481 +#> 314 B1 95.959596 4.575859481 +#> 315 B1 96.969697 4.498102737 +#> 316 B1 97.979798 4.421430686 +#> 317 B1 98.989899 4.345840882 +#> 318 B1 100.000000 4.271330056 +#> 319 C1 0.000000 0.000000000 +#> 320 C1 1.000000 1.829645786 +#> 321 C1 1.010101 1.847087763 +#> 322 C1 2.020202 3.492133303 +#> 323 C1 3.000000 4.910531064 +#> 324 C1 3.030303 4.951772742 +#> 325 C1 4.040404 6.241420142 +#> 326 C1 5.050505 7.375351980 +#> 327 C1 6.060606 8.366785999 +#> 328 C1 7.000000 9.171671206 +#> 329 C1 7.070707 9.227954769 +#> 330 C1 8.080808 9.970174354 +#> 331 C1 9.090909 10.603908370 +#> 332 C1 10.101010 11.138827767 +#> 333 C1 11.111111 11.583866567 +#> 334 C1 12.121212 11.947273869 +#> 335 C1 13.131313 12.236662337 +#> 336 C1 14.000000 12.431704739 +#> 337 C1 14.141414 12.459053419 +#> 338 C1 15.151515 12.620919488 +#> 339 C1 16.161616 12.728223141 +#> 340 C1 17.171717 12.786453805 +#> 341 C1 18.181818 12.800661859 +#> 342 C1 19.191919 12.775490422 +#> 343 C1 20.202020 12.715204956 +#> 344 C1 21.212121 12.623720845 +#> 345 C1 22.222222 12.504629065 +#> 346 C1 23.232323 12.361220091 +#> 347 C1 24.242424 12.196506142 +#> 348 C1 25.252525 12.013241882 +#> 349 C1 26.262626 11.813943686 +#> 350 C1 27.272727 11.600907551 +#> 351 C1 28.282828 11.376225763 +#> 352 C1 29.292929 11.141802382 +#> 353 C1 30.000000 10.972842888 +#> 354 C1 30.303030 10.899367648 +#> 355 C1 31.313131 10.650491354 +#> 356 C1 32.323232 10.396595286 +#> 357 C1 33.333333 10.138964763 +#> 358 C1 34.343434 9.878759358 +#> 359 C1 35.353535 9.617022857 +#> 360 C1 36.363636 9.354692485 +#> 361 C1 37.373737 9.092607481 +#> 362 C1 38.383838 8.831517041 +#> 363 C1 39.393939 8.572087685 +#> 364 C1 40.404040 8.314910084 +#> 365 C1 41.414141 8.060505385 +#> 366 C1 42.424242 7.809331068 +#> 367 C1 43.434343 7.561786371 +#> 368 C1 44.444444 7.318217302 +#> 369 C1 45.454545 7.078921287 +#> 370 C1 46.464646 6.844151456 +#> 371 C1 47.474747 6.614120611 +#> 372 C1 48.484848 6.389004885 +#> 373 C1 49.494949 6.168947129 +#> 374 C1 50.505051 5.954060026 +#> 375 C1 51.515152 5.744428970 +#> 376 C1 52.525253 5.540114721 +#> 377 C1 53.535354 5.341155842 +#> 378 C1 54.545455 5.147570951 +#> 379 C1 55.555556 4.959360784 +#> 380 C1 56.565657 4.776510102 +#> 381 C1 57.575758 4.598989433 +#> 382 C1 58.585859 4.426756673 +#> 383 C1 59.595960 4.259758556 +#> 384 C1 60.606061 4.097932000 +#> 385 C1 61.616162 3.941205338 +#> 386 C1 62.000000 3.882970158 +#> 387 C1 62.626263 3.789499444 +#> 388 C1 63.636364 3.642728760 +#> 389 C1 64.646465 3.500802233 +#> 390 C1 65.656566 3.363624171 +#> 391 C1 66.666667 3.231095021 +#> 392 C1 67.676768 3.103112069 +#> 393 C1 68.686869 2.979570086 +#> 394 C1 69.696970 2.860361903 +#> 395 C1 70.707071 2.745378939 +#> 396 C1 71.717172 2.634511667 +#> 397 C1 72.727273 2.527650041 +#> 398 C1 73.737374 2.424683880 +#> 399 C1 74.747475 2.325503203 +#> 400 C1 75.757576 2.229998536 +#> 401 C1 76.767677 2.138061182 +#> 402 C1 77.777778 2.049583458 +#> 403 C1 78.787879 1.964458908 +#> 404 C1 79.797980 1.882582485 +#> 405 C1 80.808081 1.803850715 +#> 406 C1 81.818182 1.728161832 +#> 407 C1 82.828283 1.655415900 +#> 408 C1 83.838384 1.585514911 +#> 409 C1 84.848485 1.518362874 +#> 410 C1 85.858586 1.453865880 +#> 411 C1 86.868687 1.391932162 +#> 412 C1 87.878788 1.332472134 +#> 413 C1 88.888889 1.275398429 +#> 414 C1 89.898990 1.220625918 +#> 415 C1 90.909091 1.168071723 +#> 416 C1 91.919192 1.117655227 +#> 417 C1 92.929293 1.069298066 +#> 418 C1 93.939394 1.022924125 +#> 419 C1 94.949495 0.978459525 +#> 420 C1 95.959596 0.935832597 +#> 421 C1 96.969697 0.894973866 +#> 422 C1 97.979798 0.855816021 +#> 423 C1 98.989899 0.818293881 +#> 424 C1 100.000000 0.782344364 +#> 425 A2 0.000000 0.000000000 +#> 426 A2 1.000000 0.005272357 +#> 427 A2 1.010101 0.005377817 +#> 428 A2 2.020202 0.020885524 +#> 429 A2 3.000000 0.044759575 +#> 430 A2 3.030303 0.045628064 +#> 431 A2 4.040404 0.078765936 +#> 432 A2 5.050505 0.119512155 +#> 433 A2 6.060606 0.167129381 +#> 434 A2 7.000000 0.216973934 +#> 435 A2 7.070707 0.220927189 +#> 436 A2 8.080808 0.280259484 +#> 437 A2 9.090909 0.344522046 +#> 438 A2 10.101010 0.413150206 +#> 439 A2 11.111111 0.485616641 +#> 440 A2 12.121212 0.561429288 +#> 441 A2 13.131313 0.640129357 +#> 442 A2 14.000000 0.709794102 +#> 443 A2 14.141414 0.721289460 +#> 444 A2 15.151515 0.804511827 +#> 445 A2 16.161616 0.889426625 +#> 446 A2 17.171717 0.975690359 +#> 447 A2 18.181818 1.062984358 +#> 448 A2 19.191919 1.151013342 +#> 449 A2 20.202020 1.239504068 +#> 450 A2 21.212121 1.328204041 +#> 451 A2 22.222222 1.416880297 +#> 452 A2 23.232323 1.505318253 +#> 453 A2 24.242424 1.593320615 +#> 454 A2 25.252525 1.680706344 +#> 455 A2 26.262626 1.767309680 +#> 456 A2 27.272727 1.852979219 +#> 457 A2 28.282828 1.937577034 +#> 458 A2 29.292929 2.020977853 +#> 459 A2 30.000000 2.078585030 +#> 460 A2 30.303030 2.103068270 +#> 461 A2 31.313131 2.183746011 +#> 462 A2 32.323232 2.262919231 +#> 463 A2 33.333333 2.340505852 +#> 464 A2 34.343434 2.416432940 +#> 465 A2 35.353535 2.490636111 +#> 466 A2 36.363636 2.563058979 +#> 467 A2 37.373737 2.633652622 +#> 468 A2 38.383838 2.702375089 +#> 469 A2 39.393939 2.769190926 +#> 470 A2 40.404040 2.834070737 +#> 471 A2 41.414141 2.896990764 +#> 472 A2 42.424242 2.957932489 +#> 473 A2 43.434343 3.016882265 +#> 474 A2 44.444444 3.073830964 +#> 475 A2 45.454545 3.128773647 +#> 476 A2 46.464646 3.181709250 +#> 477 A2 47.474747 3.232640290 +#> 478 A2 48.484848 3.281572591 +#> 479 A2 49.494949 3.328515022 +#> 480 A2 50.505051 3.373479253 +#> 481 A2 51.515152 3.416479521 +#> 482 A2 52.525253 3.457532417 +#> 483 A2 53.535354 3.496656681 +#> 484 A2 54.545455 3.533873012 +#> 485 A2 55.555556 3.569203883 +#> 486 A2 56.565657 3.602673379 +#> 487 A2 57.575758 3.634307034 +#> 488 A2 58.585859 3.664131686 +#> 489 A2 59.595960 3.692175334 +#> 490 A2 60.606061 3.718467012 +#> 491 A2 61.616162 3.743036663 +#> 492 A2 62.000000 3.751927986 +#> 493 A2 62.626263 3.765915028 +#> 494 A2 63.636364 3.787133539 +#> 495 A2 64.646465 3.806724217 +#> 496 A2 65.656566 3.824719582 +#> 497 A2 66.666667 3.841152565 +#> 498 A2 67.676768 3.856056426 +#> 499 A2 68.686869 3.869464684 +#> 500 A2 69.696970 3.881411040 +#> 501 A2 70.707071 3.891929316 +#> 502 A2 71.717172 3.901053396 +#> 503 A2 72.727273 3.908817168 +#> 504 A2 73.737374 3.915254472 +#> 505 A2 74.747475 3.920399054 +#> 506 A2 75.757576 3.924284521 +#> 507 A2 76.767677 3.926944303 +#> 508 A2 77.777778 3.928411610 +#> 509 A2 78.787879 3.928719404 +#> 510 A2 79.797980 3.927900364 +#> 511 A2 80.808081 3.925986861 +#> 512 A2 81.818182 3.923010926 +#> 513 A2 82.828283 3.919004234 +#> 514 A2 83.838384 3.913998077 +#> 515 A2 84.848485 3.908023347 +#> 516 A2 85.858586 3.901110518 +#> 517 A2 86.868687 3.893289633 +#> 518 A2 87.878788 3.884590288 +#> 519 A2 88.888889 3.875041619 +#> 520 A2 89.898990 3.864672297 +#> 521 A2 90.909091 3.853510511 +#> 522 A2 91.919192 3.841583970 +#> 523 A2 92.929293 3.828919886 +#> 524 A2 93.939394 3.815544978 +#> 525 A2 94.949495 3.801485462 +#> 526 A2 95.959596 3.786767051 +#> 527 A2 96.969697 3.771414951 +#> 528 A2 97.979798 3.755453860 +#> 529 A2 98.989899 3.738907968 +#> 530 A2 100.000000 3.721800959 +#> +#> $cost +#> function (P) +#> { +#> assign("calls", calls + 1, inherits = TRUE) +#> if (trace_parms) +#> cat(P, "\n") +#> if (length(state.ini.optim) > 0) { +#> odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed) +#> names(odeini) <- c(state.ini.optim.boxnames, state.ini.fixed.boxnames) +#> } +#> else { +#> odeini <- state.ini.fixed +#> names(odeini) <- state.ini.fixed.boxnames +#> } +#> odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], +#> transparms.fixed) +#> parms <- backtransform_odeparms(odeparms, mkinmod, transform_rates = transform_rates, +#> transform_fractions = transform_fractions) +#> out <- mkinpredict(mkinmod, parms, odeini, outtimes, solution_type = solution_type, +#> use_compiled = use_compiled, method.ode = method.ode, +#> atol = atol, rtol = rtol, ...) +#> assign("out_predicted", out, inherits = TRUE) +#> mC <- modCost(out, observed, y = "value", err = err, weight = weight, +#> scaleVar = scaleVar) +#> if (mC$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: 0x36a83b0> +#> +#> $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: 0x36a83b0> +#> +#> $hessian_notrans +#> parent_0 k_parent k_A1 k_B1 +#> parent_0 7.365081 -1854.5113 -7.186039e+02 -1.307858e+02 +#> k_parent -1854.511330 2686790.7676 -6.235542e+04 -1.429363e+04 +#> k_A1 -718.603865 -62355.4211 3.128242e+06 0.000000e+00 +#> k_B1 -130.785796 -14293.6348 0.000000e+00 4.545506e+05 +#> k_C1 -76.404274 -38575.9391 1.190516e-02 -9.422820e-04 +#> k_A2 -17.933942 -4390.5079 -5.838973e+04 0.000000e+00 +#> f_parent_to_A1 75.150866 43257.2599 -1.733841e+05 0.000000e+00 +#> f_parent_to_B1 29.265575 17940.1132 0.000000e+00 -6.150198e+04 +#> f_parent_to_C1 20.661354 19692.5582 -6.146186e-05 -1.990817e-03 +#> f_A1_to_A2 1.593279 597.0744 5.849840e+03 0.000000e+00 +#> k_C1 k_A2 f_parent_to_A1 f_parent_to_B1 +#> parent_0 -7.640427e+01 -1.793394e+01 7.515087e+01 2.926558e+01 +#> k_parent -3.857594e+04 -4.390508e+03 4.325726e+04 1.794011e+04 +#> k_A1 1.190516e-02 -5.838973e+04 -1.733841e+05 0.000000e+00 +#> k_B1 -9.422820e-04 0.000000e+00 0.000000e+00 -6.150198e+04 +#> k_C1 8.855106e+04 4.105787e-04 -1.354551e-03 5.852620e-04 +#> k_A2 4.105787e-04 4.649850e+04 -4.327086e+03 0.000000e+00 +#> f_parent_to_A1 -1.354551e-03 -4.327086e+03 1.813234e+04 0.000000e+00 +#> f_parent_to_B1 5.852620e-04 0.000000e+00 0.000000e+00 1.376213e+04 +#> f_parent_to_C1 -1.658031e+04 2.903794e-04 1.946385e-03 1.325258e-03 +#> f_A1_to_A2 -4.367402e-05 -3.679910e+03 3.844249e+02 0.000000e+00 +#> f_parent_to_C1 f_A1_to_A2 +#> parent_0 2.066135e+01 1.593279e+00 +#> k_parent 1.969256e+04 5.970744e+02 +#> k_A1 -6.146186e-05 5.849840e+03 +#> k_B1 -1.990817e-03 0.000000e+00 +#> k_C1 -1.658031e+04 -4.367402e-05 +#> k_A2 2.903794e-04 -3.679910e+03 +#> f_parent_to_A1 1.946385e-03 3.844249e+02 +#> f_parent_to_B1 1.325258e-03 0.000000e+00 +#> f_parent_to_C1 4.483759e+03 -3.796730e-05 +#> f_A1_to_A2 -3.796730e-05 3.269288e+02 +#> +#> $start +#> value type +#> parent_0 93.2000000 state +#> k_parent 0.1000000 deparm +#> k_A1 0.1001000 deparm +#> k_B1 0.1002000 deparm +#> k_C1 0.1003000 deparm +#> k_A2 0.1004000 deparm +#> f_parent_to_A1 0.3333333 deparm +#> f_parent_to_B1 0.3333333 deparm +#> f_parent_to_C1 0.3333333 deparm +#> f_A1_to_A2 0.5000000 deparm +#> +#> $start_transformed +#> value lower upper +#> parent_0 93.200000 -Inf Inf +#> log_k_parent -2.302585 -Inf Inf +#> log_k_A1 -2.301586 -Inf Inf +#> log_k_B1 -2.300587 -Inf Inf +#> log_k_C1 -2.299590 -Inf Inf +#> log_k_A2 -2.298593 -Inf Inf +#> f_parent_ilr_1 0.000000 -Inf Inf +#> f_parent_ilr_2 0.000000 -Inf Inf +#> f_A1_ilr_1 0.000000 -Inf Inf +#> +#> $fixed +#> value type +#> A1_0 0 state +#> B1_0 0 state +#> C1_0 0 state +#> A2_0 0 state +#> +#> $data +#> time variable observed predicted residual +#> 1 0 parent 93.20 91.918159794 1.2818402 +#> 2 1 parent 89.40 87.462788491 1.9372115 +#> 3 3 parent 79.70 79.189448055 0.5105519 +#> 4 7 parent 61.10 64.916531757 -3.8165318 +#> 5 14 parent 48.20 45.846828365 2.3531716 +#> 6 30 parent 15.90 20.704334210 -4.8043342 +#> 7 62 parent 6.50 4.222456793 2.2775432 +#> 8 100 parent 6.00 0.639147580 5.3608524 +#> 9 0 A1 NA 0.000000000 NA +#> 10 1 A1 NA 1.685461006 NA +#> 11 3 A1 0.55 4.746752202 -4.1967522 +#> 12 7 A1 6.87 9.773298725 -2.9032987 +#> 13 14 A1 17.08 15.767512526 1.3124875 +#> 14 30 A1 21.68 21.077890710 0.6021093 +#> 15 62 A1 15.77 18.279232408 -2.5092324 +#> 16 100 A1 13.63 11.743860400 1.8861396 +#> 17 0 B1 NA 0.000000000 NA +#> 18 1 B1 NA 0.862762059 NA +#> 19 3 B1 NA 2.418226457 NA +#> 20 7 B1 0.55 4.930176837 -4.3801768 +#> 21 14 B1 2.31 7.810248132 -5.5002481 +#> 22 30 B1 15.76 9.968281596 5.7917184 +#> 23 62 B1 6.36 7.745265792 -1.3852658 +#> 24 100 B1 3.74 4.271330056 -0.5313301 +#> 25 0 C1 NA 0.000000000 NA +#> 26 1 C1 0.55 1.829645786 -1.2796458 +#> 27 3 C1 3.20 4.910531064 -1.7105311 +#> 28 7 C1 5.46 9.171671206 -3.7116712 +#> 29 14 C1 12.55 12.431704739 0.1182953 +#> 30 30 C1 10.45 10.972842888 -0.5228429 +#> 31 62 C1 4.74 3.882970158 0.8570298 +#> 32 100 C1 4.33 0.782344364 3.5476556 +#> 33 0 A2 NA 0.000000000 NA +#> 34 1 A2 0.55 0.005272357 0.5447276 +#> 35 3 A2 1.41 0.044759575 1.3652404 +#> 36 7 A2 0.55 0.216973934 0.3330261 +#> 37 14 A2 1.29 0.709794102 0.5802059 +#> 38 30 A2 1.95 2.078585030 -0.1285850 +#> 39 62 A2 3.54 3.751927986 -0.2119280 +#> 40 100 A2 3.86 3.721800959 0.1381990 +#> +#> $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 k_A1 k_B1 k_C1 +#> 91.91815979 0.04968519 0.01393165 0.01859846 0.06171564 +#> k_A2 f_parent_to_A1 f_parent_to_B1 f_parent_to_C1 f_A1_to_A2 +#> 0.02431549 0.38096192 0.19546676 0.42357132 0.44796066 +#> +#> $bparms.fixed +#> A1_0 B1_0 C1_0 A2_0 +#> 0 0 0 0 +#> +#> $bparms.ode +#> k_parent f_parent_to_A1 f_parent_to_B1 f_parent_to_C1 k_A1 +#> 0.04968519 0.38096192 0.19546676 0.42357132 0.01393165 +#> f_A1_to_A2 k_B1 k_C1 k_A2 +#> 0.44796066 0.01859846 0.06171564 0.02431549 +#> +#> $bparms.state +#> parent A1 B1 C1 A2 +#> 91.91816 0.00000 0.00000 0.00000 0.00000 +#> +#> $date +#> [1] "Fri Nov 18 15:20:45 2016" +#> +#> attr(,"class") +#> [1] "mkinfit" "modFit"
#> Successfully compiled differential equation model from auto-generated C code.
+fit.ff <- mkinfit(SFO_SFO.ff, FOCUS_2006_D)
#> Model cost at call 1 : 15156.12 +#> Model cost at call 2 : 15156.12 +#> Model cost at call 6 : 8243.644 +#> Model cost at call 12 : 6290.714 +#> Model cost at call 13 : 6290.684 +#> Model cost at call 15 : 6290.453 +#> Model cost at call 18 : 1700.75 +#> Model cost at call 20 : 1700.612 +#> Model cost at call 24 : 1190.923 +#> Model cost at call 26 : 1190.922 +#> Model cost at call 29 : 1017.417 +#> Model cost at call 31 : 1017.417 +#> Model cost at call 33 : 1017.416 +#> Model cost at call 34 : 644.0471 +#> Model cost at call 36 : 644.0469 +#> Model cost at call 38 : 644.0468 +#> Model cost at call 39 : 590.5024 +#> Model cost at call 41 : 590.5021 +#> Model cost at call 43 : 590.5015 +#> Model cost at call 44 : 543.2187 +#> Model cost at call 45 : 543.2183 +#> Model cost at call 46 : 543.2182 +#> Model cost at call 50 : 391.348 +#> Model cost at call 51 : 391.3479 +#> Model cost at call 56 : 386.4789 +#> Model cost at call 58 : 386.4789 +#> Model cost at call 60 : 386.4779 +#> Model cost at call 61 : 384.0686 +#> Model cost at call 63 : 384.0686 +#> Model cost at call 66 : 382.7812 +#> Model cost at call 68 : 382.7812 +#> Model cost at call 70 : 382.7812 +#> Model cost at call 71 : 378.9272 +#> Model cost at call 73 : 378.9272 +#> Model cost at call 75 : 378.9272 +#> Model cost at call 76 : 377.4846 +#> Model cost at call 78 : 377.4846 +#> Model cost at call 81 : 375.9738 +#> Model cost at call 83 : 375.9738 +#> Model cost at call 86 : 375.3387 +#> Model cost at call 88 : 375.3387 +#> Model cost at call 91 : 374.5774 +#> Model cost at call 93 : 374.5774 +#> Model cost at call 95 : 374.5774 +#> Model cost at call 96 : 373.5447 +#> Model cost at call 100 : 373.5446 +#> Model cost at call 102 : 373.2643 +#> Model cost at call 104 : 373.2643 +#> Model cost at call 107 : 372.6799 +#> Model cost at call 111 : 372.6798 +#> Model cost at call 114 : 372.6325 +#> Model cost at call 116 : 372.6325 +#> Model cost at call 119 : 372.6159 +#> Model cost at call 121 : 372.6159 +#> Model cost at call 123 : 372.6159 +#> Model cost at call 124 : 372.5845 +#> Model cost at call 126 : 372.5845 +#> Model cost at call 129 : 372.5375 +#> Model cost at call 130 : 372.4771 +#> Model cost at call 131 : 372.2008 +#> Model cost at call 132 : 371.4923 +#> Model cost at call 134 : 371.4923 +#> Model cost at call 137 : 371.3022 +#> Model cost at call 139 : 371.3022 +#> Model cost at call 143 : 371.2271 +#> Model cost at call 144 : 371.2271 +#> Model cost at call 148 : 371.2202 +#> Model cost at call 149 : 371.215 +#> Model cost at call 152 : 371.215 +#> Model cost at call 154 : 371.2136 +#> Model cost at call 155 : 371.2136 +#> Model cost at call 156 : 371.2136 +#> Model cost at call 160 : 371.2134 +#> Model cost at call 164 : 371.2134 +#> Model cost at call 167 : 371.2134 +#> Optimisation by method Port successfully terminated.
summary(fit.ff, data = FALSE)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:20:52 2016 +#> Date of summary: Fri Nov 18 15:20:52 2016 +#> +#> 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 185 model solutions performed in 0.764 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 +#> 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 99.60000 1.61400 96.3300 102.9000 +#> log_k_parent -2.31600 0.04187 -2.4010 -2.2310 +#> log_k_m1 -5.24800 0.13610 -5.5230 -4.9720 +#> f_parent_ilr_1 0.04096 0.06477 -0.0904 0.1723 +#> +#> Parameter correlation: +#> parent_0 log_k_parent log_k_m1 f_parent_ilr_1 +#> parent_0 1.0000 0.5178 -0.1701 -0.5489 +#> log_k_parent 0.5178 1.0000 -0.3285 -0.5451 +#> log_k_m1 -0.1701 -0.3285 1.0000 0.7466 +#> f_parent_ilr_1 -0.5489 -0.5451 0.7466 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 0.098700 23.880 5.701e-24 0.090660 1.074e-01 +#> k_m1 0.005261 7.349 5.758e-09 0.003992 6.933e-03 +#> f_parent_to_m1 0.514500 22.490 4.374e-23 0.468100 5.606e-01 +#> +#> Chi2 error levels in percent: +#> err.min n.optim df +#> All data 6.398 4 15 +#> parent 6.459 2 7 +#> m1 4.690 2 8 +#> +#> Resulting formation fractions: +#> ff +#> parent_m1 0.5145 +#> parent_sink 0.4855 +#> +#> Estimated disappearance times: +#> DT50 DT90 +#> parent 7.023 23.33 +#> m1 131.761 437.70
initials <- c("f_parent_to_m1" = 0.5) +transformed <- transform_odeparms(initials, SFO_SFO.ff) +backtransform_odeparms(transformed, SFO_SFO.ff)
#> f_parent_to_m1 +#> 0.5
+# And without sink +SFO_SFO.ff.2 <- mkinmod( + parent = list(type = "SFO", to = "m1", sink = FALSE), + m1 = list(type = "SFO"), + use_of_ff = "max")
#> Successfully compiled differential equation model from auto-generated C code.
+ +fit.ff.2 <- mkinfit(SFO_SFO.ff.2, FOCUS_2006_D)
#> Model cost at call 1 : 12435.14 +#> Model cost at call 2 : 12435.14 +#> Model cost at call 5 : 8276.306 +#> Model cost at call 6 : 8276.294 +#> Model cost at call 7 : 8275.676 +#> Model cost at call 9 : 5256.953 +#> Model cost at call 11 : 5256.951 +#> Model cost at call 12 : 5256.943 +#> Model cost at call 14 : 4469.745 +#> Model cost at call 18 : 4462.927 +#> Model cost at call 21 : 4462.925 +#> Model cost at call 22 : 4376.059 +#> Model cost at call 24 : 4376.058 +#> Model cost at call 27 : 4366.956 +#> Model cost at call 29 : 4366.956 +#> Model cost at call 31 : 4365.275 +#> Model cost at call 33 : 4365.275 +#> Model cost at call 35 : 4351.877 +#> Model cost at call 37 : 4351.877 +#> Model cost at call 39 : 4338.109 +#> Model cost at call 41 : 4338.109 +#> Model cost at call 43 : 4297.053 +#> Model cost at call 44 : 4218.591 +#> Model cost at call 45 : 3940.397 +#> Model cost at call 46 : 3690.395 +#> Model cost at call 48 : 3690.395 +#> Model cost at call 49 : 3690.385 +#> Model cost at call 50 : 3038.366 +#> Model cost at call 53 : 3038.365 +#> Model cost at call 54 : 2637.866 +#> Model cost at call 57 : 2637.865 +#> Model cost at call 59 : 2588.01 +#> Model cost at call 60 : 2588.009 +#> Model cost at call 63 : 2576.742 +#> Model cost at call 66 : 2576.742 +#> Model cost at call 67 : 2574 +#> Model cost at call 68 : 2574 +#> Model cost at call 69 : 2574 +#> Model cost at call 71 : 2569.76 +#> Model cost at call 73 : 2569.76 +#> Model cost at call 74 : 2569.76 +#> Model cost at call 75 : 2569.403 +#> Model cost at call 76 : 2569.403 +#> Model cost at call 79 : 2569.4 +#> Model cost at call 80 : 2569.4 +#> Model cost at call 81 : 2569.4 +#> Model cost at call 83 : 2569.4 +#> Model cost at call 86 : 2569.4 +#> Model cost at call 90 : 2569.4 +#> Model cost at call 99 : 2569.4 +#> Model cost at call 100 : 2569.4 +#> Optimisation by method Port successfully terminated.
summary(fit.ff.2, data = FALSE)
#> mkin version: 0.9.44.9000 +#> R version: 3.3.2 +#> Date of fit: Fri Nov 18 15:20:52 2016 +#> Date of summary: Fri Nov 18 15:20:52 2016 +#> +#> 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 0.44 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 0.11059 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
+