From 0b98c459c30a0629a728acf6b311de035c55fb64 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 18 Jul 2018 15:18:30 +0200 Subject: Correct references to the Rocke and Lorenzato model Rename 'sigma_rl' to 'sigma_twocomp' as the Rocke and Lorenzato model assumes lognormal distribution for large y. Rebuild static documentation. --- .Rbuildignore | 1 + DESCRIPTION | 2 +- NEWS.md | 2 + R/mkinfit.R | 6 +- R/sigma_rl.R | 3 - R/sigma_twocomp.R | 3 + README.html | 2 +- README.md | 6 +- _pkgdown.yml | 2 +- build.log | 2 +- check.log | 15 +- docs/articles/FOCUS_D.html | 12 +- docs/articles/FOCUS_L.html | 60 +- docs/articles/FOCUS_Z.html | 4 +- docs/articles/compiled_models.html | 18 +- docs/articles/index.html | 2 +- docs/articles/mkin.html | 4 +- docs/articles/twa.html | 4 +- docs/authors.html | 2 +- docs/index.html | 4 +- docs/news/index.html | 12 +- docs/reference/DFOP.solution.html | 2 +- docs/reference/Extract.mmkin.html | 18 +- docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html | 2 +- docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html | 2 +- docs/reference/FOCUS_2006_HS_ref_A_to_F.html | 2 +- docs/reference/FOCUS_2006_SFO_ref_A_to_F.html | 2 +- docs/reference/FOCUS_2006_datasets.html | 2 +- docs/reference/FOMC.solution.html | 2 +- docs/reference/HS.solution.html | 2 +- docs/reference/IORE.solution.html | 4 +- docs/reference/SFO.solution.html | 2 +- docs/reference/SFORB.solution.html | 2 +- docs/reference/add_err.html | 2 +- docs/reference/endpoints.html | 2 +- docs/reference/geometric_mean.html | 2 +- docs/reference/ilr.html | 2 +- docs/reference/index.html | 6 +- docs/reference/max_twa_parent.html | 2 +- docs/reference/mccall81_245T.html | 12 +- docs/reference/mkin_long_to_wide.html | 2 +- docs/reference/mkin_wide_to_long.html | 2 +- docs/reference/mkinds.html | 2 +- docs/reference/mkinerrmin.html | 2 +- docs/reference/mkinfit.html | 23 +- docs/reference/mkinmod.html | 2 +- docs/reference/mkinparplot.html | 2 +- docs/reference/mkinplot.html | 2 +- docs/reference/mkinpredict.html | 4 +- docs/reference/mkinresplot.html | 2 +- docs/reference/mkinsub.html | 2 +- docs/reference/mmkin.html | 2 +- docs/reference/plot.mkinfit.html | 2 +- docs/reference/plot.mmkin.html | 2 +- docs/reference/print.mkinds.html | 2 +- docs/reference/print.mkinmod.html | 2 +- docs/reference/schaefer07_complex_case.html | 2 +- docs/reference/sigma_rl.html | 2 +- docs/reference/sigma_twocomp.html | 203 +++++++ docs/reference/summary.mkinfit.html | 12 +- docs/reference/synthetic_data_for_UBA.html | 12 +- docs/reference/test_data_from_UBA_2014.html | 2 +- docs/reference/transform_odeparms.html | 12 +- man/mkinfit.Rd | 9 +- man/sigma_rl.Rd | 26 - man/sigma_twocomp.Rd | 34 ++ man/synthetic_data_for_UBA.Rd | 5 +- vignettes/FOCUS_D.html | 104 ++-- vignettes/FOCUS_L.html | 771 +++++++++++-------------- vignettes/FOCUS_Z.html | 84 +-- vignettes/compiled_models.html | 20 +- 71 files changed, 867 insertions(+), 722 deletions(-) delete mode 100644 R/sigma_rl.R create mode 100644 R/sigma_twocomp.R create mode 100644 docs/reference/sigma_twocomp.html delete mode 100644 man/sigma_rl.Rd create mode 100644 man/sigma_twocomp.Rd diff --git a/.Rbuildignore b/.Rbuildignore index 5125a068..da90d9b6 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -24,5 +24,6 @@ ^vignettes/FOCUS_Z.tex$ ^vignettes/mkin.tex$ ^mkin_.*\.tar\.gz +^mkin.tar$ ^docs$ ^_pkgdown\.yml$ diff --git a/DESCRIPTION b/DESCRIPTION index 10f2b948..dd5e31b6 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -2,7 +2,7 @@ Package: mkin Type: Package Title: Kinetic Evaluation of Chemical Degradation Data Version: 0.9.47.2 -Date: 2018-07-04 +Date: 2018-07-18 Authors@R: c(person("Johannes", "Ranke", role = c("aut", "cre", "cph"), email = "jranke@uni-bremen.de", comment = c(ORCID = "0000-0003-4371-6538")), diff --git a/NEWS.md b/NEWS.md index bee80efb..1c1adb09 100644 --- a/NEWS.md +++ b/NEWS.md @@ -1,5 +1,7 @@ # mkin 0.9.47.2 +- 'sigma_twocomp': Rename 'sigma_rl' to 'sigma_twocomp' as the Rocke and Lorenzato model assumes lognormal distribution for large y. Correct references to the Rocke and Lorenzato model accordingly. + - 'mkinfit': Use 1.1 as starting value for N parameter of IORE models to obtain convergence in more difficult cases. Show parameter names when 'trace_parms' is 'TRUE'. # mkin 0.9.47.1 (2018-02-06) diff --git a/R/mkinfit.R b/R/mkinfit.R index 840faf53..92b455f7 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -259,7 +259,7 @@ mkinfit <- function(mkinmod, observed, weight.ini <- weight <- match.arg(weight) if (weight.ini == "tc") { - observed$err = sigma_rl(observed$value, tc["sigma_low"], tc["rsd_high"]) + observed$err = sigma_twocomp(observed$value, tc["sigma_low"], tc["rsd_high"]) err <- "err" } else { if (!is.null(err)) weight.ini = "manual" @@ -415,7 +415,7 @@ mkinfit <- function(mkinmod, observed, # We need unweighted residuals to update the weighting cost_tmp <- cost(fit$par) - tc_fit <- nls(abs(res.unweighted) ~ sigma_rl(obs, sigma_low, rsd_high), + tc_fit <- nls(abs(res.unweighted) ~ sigma_twocomp(obs, sigma_low, rsd_high), start = list(sigma_low = tc["sigma_low"], rsd_high = tc["rsd_high"]), data = cost_tmp$residuals, algorithm = "port") @@ -453,7 +453,7 @@ mkinfit <- function(mkinmod, observed, if (reweight.method == "tc") { cost_tmp <- cost(fit$par) - tc_fit <- nls(abs(res.unweighted) ~ sigma_rl(obs, sigma_low, rsd_high), + tc_fit <- nls(abs(res.unweighted) ~ sigma_twocomp(obs, sigma_low, rsd_high), start = as.list(tc_fitted), data = cost_tmp$residuals, algorithm = "port") diff --git a/R/sigma_rl.R b/R/sigma_rl.R deleted file mode 100644 index 2b921d29..00000000 --- a/R/sigma_rl.R +++ /dev/null @@ -1,3 +0,0 @@ - sigma_rl <- function(y, sigma_low, rsd_high) { - sqrt(sigma_low^2 + y^2 * rsd_high^2) - } diff --git a/R/sigma_twocomp.R b/R/sigma_twocomp.R new file mode 100644 index 00000000..b06816c1 --- /dev/null +++ b/R/sigma_twocomp.R @@ -0,0 +1,3 @@ + sigma_twocomp <- function(y, sigma_low, rsd_high) { + sqrt(sigma_low^2 + y^2 * rsd_high^2) + } diff --git a/README.html b/README.html index c9f86c6b..f71dcfbc 100644 --- a/README.html +++ b/README.html @@ -155,7 +155,7 @@ $(document).ready(function () {
  • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
  • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
  • Iteratively reweighted least squares fitting is implemented in a similar way as in KinGUII and CAKE (see below). Simply add the argument reweight.method = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.
    • -
  • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
    • +
  • Iterative reweighting is also possible using a two-component error model for analytical data similar to the one proposed by Rocke and Lorenzato using the argument reweight.method = "tc".
  • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
    • diff --git a/README.md b/README.md index 26cdcafb..f3a0728b 100644 --- a/README.md +++ b/README.md @@ -89,9 +89,9 @@ and at [R-Forge](http://kinfit.r-forge.r-project.org/mkin_static/index.html). `reweight.method = "obs"` to your call to `mkinfit` and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged. -* Iterative reweighting is also possible using the two-component error model - for analytical data of - [Rocke and Lorenzato](https://pkgdown.jrwb.de/mkin/reference/sigma_rl.html) +* Iterative reweighting is also possible using a two-component error model + for analytical data similar to the one proposed by + [Rocke and Lorenzato](https://pkgdown.jrwb.de/mkin/reference/sigma_twocomp.html) using the argument `reweight.method = "tc"`. * When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite. diff --git a/_pkgdown.yml b/_pkgdown.yml index 2630bca0..9cb51f5c 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -48,7 +48,7 @@ reference: - print.mkinmod - transform_odeparms - ilr - - sigma_rl + - sigma_twocomp - title: Analytical solutions desc: Parent only model solutions contents: diff --git a/build.log b/build.log index 67f4433b..8cc3a3f5 100644 --- a/build.log +++ b/build.log @@ -6,5 +6,5 @@ * checking for LF line-endings in source and make files and shell scripts * checking for empty or unneeded directories * looking to see if a ‘data/datalist’ file should be added -* building ‘mkin_0.9.47.1.tar.gz’ +* building ‘mkin_0.9.47.2.tar.gz’ diff --git a/check.log b/check.log index 289ad803..909cc752 100644 --- a/check.log +++ b/check.log @@ -1,14 +1,16 @@ * using log directory ‘/home/jranke/git/mkin/mkin.Rcheck’ -* using R version 3.4.3 (2017-11-30) +* using R version 3.5.1 (2018-07-02) * using platform: x86_64-pc-linux-gnu (64-bit) * using session charset: UTF-8 * using options ‘--no-tests --as-cran’ * checking for file ‘mkin/DESCRIPTION’ ... OK * checking extension type ... Package -* this is package ‘mkin’ version ‘0.9.47.1’ +* this is package ‘mkin’ version ‘0.9.47.2’ * package encoding: UTF-8 -* checking CRAN incoming feasibility ... Note_to_CRAN_maintainers +* checking CRAN incoming feasibility ... NOTE Maintainer: ‘Johannes Ranke ’ + +Size of tarball: 6560750 bytes * checking package namespace information ... OK * checking package dependencies ... OK * checking if this is a source package ... OK @@ -17,6 +19,7 @@ Maintainer: ‘Johannes Ranke ’ * checking for hidden files and directories ... OK * checking for portable file names ... OK * checking for sufficient/correct file permissions ... OK +* checking serialization versions ... OK * checking whether package ‘mkin’ can be installed ... OK * checking installed package size ... OK * checking package directory ... OK @@ -39,7 +42,9 @@ HttpExceptionRequest Request { responseTimeout = ResponseTimeoutDefault requestVersion = HTTP/1.1 } - (InternalException (HandshakeFailed Error_EOF)) + ConnectionTimeout +Non-standard file/directory found at top level: + ‘mkin.tar’ * checking for left-over files ... OK * checking index information ... OK * checking package subdirectories ... OK @@ -81,7 +86,7 @@ HttpExceptionRequest Request { * checking PDF version of manual ... OK * DONE -Status: 1 WARNING +Status: 1 WARNING, 1 NOTE See ‘/home/jranke/git/mkin/mkin.Rcheck/00check.log’ for details. diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index 8a1f51d1..630b1d02 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -29,7 +29,7 @@ mkin - 0.9.47.1 + 0.9.47.2 @@ -84,7 +84,7 @@

    Example evaluation of FOCUS Example Dataset D

    Johannes Ranke

    -

    2018-06-06

    +

    2018-07-18

    @@ -161,9 +161,9 @@

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

    summary(fit)
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:49 2018 
-## Date of summary: Wed Jun  6 01:21:50 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 14:52:30 2018 
+## Date of summary: Wed Jul 18 14:52:31 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -171,7 +171,7 @@
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 0.633 s
+## Fitted with method Port using 153 model solutions performed in 0.604 s
 ## 
 ## Weighting: none
 ## 
diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html
index fcd0719d..72c293b9 100644
--- a/docs/articles/FOCUS_L.html
+++ b/docs/articles/FOCUS_L.html
@@ -29,7 +29,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -84,7 +84,7 @@
       
    Example evaluation of FOCUS Laboratory Data L1 to L3
    
                         
    Johannes Ranke
    
             
-            
    2018-06-06
    
+            
    2018-07-18
    
       
       
       
@@ -109,16 +109,16 @@ FOCUS_2006_L1_mkin <- 
    m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
 summary(m.L1.SFO)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:52 2018 
-## Date of summary: Wed Jun  6 01:21:52 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:17 2018 
+## Date of summary: Wed Jul 18 15:16:17 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.094 s
+## Fitted with method Port using 37 model solutions performed in 0.081 s
 ## 
 ## Weighting: none
 ## 
@@ -200,16 +200,16 @@ FOCUS_2006_L1_mkin <- 
    
 
    summary(m.L1.FOMC, data = FALSE)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:53 2018 
-## Date of summary: Wed Jun  6 01:21:53 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:19 2018 
+## Date of summary: Wed Jul 18 15:16:19 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 611 model solutions performed in 1.369 s
+## Fitted with method Port using 611 model solutions performed in 1.304 s
 ## 
 ## Weighting: none
 ## 
@@ -295,16 +295,16 @@ FOCUS_2006_L2_mkin <- 
    
 
    summary(m.L2.FOMC, data = FALSE)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:54 2018 
-## Date of summary: Wed Jun  6 01:21:54 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:19 2018 
+## Date of summary: Wed Jul 18 15:16:19 2018 
 ## 
 ## 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 0.173 s
+## Fitted with method Port using 81 model solutions performed in 0.175 s
 ## 
 ## Weighting: none
 ## 
@@ -366,9 +366,9 @@ FOCUS_2006_L2_mkin <- 
    
 
    summary(m.L2.DFOP, data = FALSE)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:55 2018 
-## Date of summary: Wed Jun  6 01:21:55 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:20 2018 
+## Date of summary: Wed Jul 18 15:16:20 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -377,7 +377,7 @@ FOCUS_2006_L2_mkin <-  
    summary(mm.L3[["DFOP", 1]])
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:56 2018 
-## Date of summary: Wed Jun  6 01:21:56 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:21 2018 
+## Date of summary: Wed Jul 18 15:16:21 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -469,7 +469,7 @@ mm.L3 <-  \(\chi^2\) error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the \(\chi^2\) test passes is slightly lower for the FOMC model. However, the difference appears negligible.
    
 
    summary(mm.L4[["SFO", 1]], data = FALSE)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:56 2018 
-## Date of summary: Wed Jun  6 01:21:57 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:22 2018 
+## Date of summary: Wed Jul 18 15:16:22 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.099 s
+## Fitted with method Port using 46 model solutions performed in 0.092 s
 ## 
 ## Weighting: none
 ## 
@@ -619,16 +619,16 @@ mm.L4 <- 
    summary(mm.L4[["FOMC", 1]], data = FALSE)
    
 
    ## mkin version used for fitting:    0.9.47.1 
-## R version used for fitting:       3.5.0 
-## Date of fit:     Wed Jun  6 01:21:57 2018 
-## Date of summary: Wed Jun  6 01:21:57 2018 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Wed Jul 18 15:16:22 2018 
+## Date of summary: Wed Jul 18 15:16:22 2018 
 ## 
 ## 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 0.146 s
+## Fitted with method Port using 66 model solutions performed in 0.137 s
 ## 
 ## Weighting: none
 ## 
diff --git a/docs/articles/FOCUS_Z.html b/docs/articles/FOCUS_Z.html
index 61425745..d8b9c961 100644
--- a/docs/articles/FOCUS_Z.html
+++ b/docs/articles/FOCUS_Z.html
@@ -29,7 +29,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -84,7 +84,7 @@
       
    Example evaluation of FOCUS dataset Z
    
                         
    Johannes Ranke
    
             
-            
    2018-06-06
    
+            
    2018-07-18
    
       
       
       
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 379176bf..183c9658 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -29,7 +29,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -84,7 +84,7 @@
       
    Performance benefit by using compiled model definitions in mkin
    
                         
    Johannes Ranke
    
             
-            
    2018-06-06
    
+            
    2018-07-18
    
       
       
       
@@ -125,14 +125,14 @@ SFO_SFO <- 
 
    
@@ -156,14 +156,14 @@ SFO_SFO <- 
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html
index 28186062..14a2f9b9 100644
--- a/docs/articles/mkin.html
+++ b/docs/articles/mkin.html
@@ -29,7 +29,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -84,7 +84,7 @@
       
    Introduction to mkin
    
                         
    Johannes Ranke
    
             
-            
    2018-06-06
    
+            
    2018-07-18
    
       
       
       
diff --git a/docs/articles/twa.html b/docs/articles/twa.html
index 53afcca3..0c5fe558 100644
--- a/docs/articles/twa.html
+++ b/docs/articles/twa.html
@@ -29,7 +29,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -84,7 +84,7 @@
       
    Calculation of time weighted average concentrations with mkin
    
                         
    Johannes Ranke
    
             
-            
    2018-06-06
    
+            
    2018-07-18
    
       
       
       
diff --git a/docs/authors.html b/docs/authors.html
index 492c3a18..b60e270c 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -58,7 +58,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/index.html b/docs/index.html
index 2a5f5107..6796cf1f 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -36,7 +36,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -127,7 +127,7 @@
 
  • Summary and plotting functions. The summary of an mkinfit object is in fact a full report that should give enough information to be able to approximately reproduce the fit with other tools.
    • 
 
  • The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable.
    • 
 
  • Iteratively reweighted least squares fitting is implemented in a similar way as in KinGUII and CAKE (see below). Simply add the argument reweight.method = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.
    • 
-
  • Iterative reweighting is also possible using the two-component error model for analytical data of Rocke and Lorenzato using the argument reweight.method = "tc".
    • 
+
  • Iterative reweighting is also possible using a two-component error model for analytical data similar to the one proposed by Rocke and Lorenzato using the argument reweight.method = "tc".
    • 
 
  • When a metabolite decline phase is not described well by SFO kinetics, SFORB kinetics can be used for the metabolite.
    • 
 
 
diff --git a/docs/news/index.html b/docs/news/index.html
index cc837f1e..7bfa82c4 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -58,7 +58,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -117,6 +117,15 @@
       
     
 
+    
    
+
    
+mkin 0.9.47.2 Unreleased 
+
    
+
      
+
    • ‘sigma_twocomp’: Rename ‘sigma_rl’ to ‘sigma_twocomp’ as the Rocke and Lorenzato model assumes lognormal distribution for large y. Correct references to the Rocke and Lorenzato model accordingly.
      • 
+
    • ‘mkinfit’: Use 1.1 as starting value for N parameter of IORE models to obtain convergence in more difficult cases. Show parameter names when ‘trace_parms’ is ‘TRUE’.
      • 
+
    
+
    
     
    
 
    
 mkin 0.9.47.1 (2018-02-06) 2018-02-06 
@@ -630,6 +639,7 @@
     
    
       
    Contents
    
       
      
+        
    • 0.9.47.2
      • 
         
    • 0.9.47.1
      • 
         
    • 0.9.46.3
      • 
         
    • 0.9.46.2
      • 
diff --git a/docs/reference/DFOP.solution.html b/docs/reference/DFOP.solution.html
index cd8f29e9..c1177306 100644
--- a/docs/reference/DFOP.solution.html
+++ b/docs/reference/DFOP.solution.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/Extract.mmkin.html b/docs/reference/Extract.mmkin.html
index deb418c2..5bc23d98 100644
--- a/docs/reference/Extract.mmkin.html
+++ b/docs/reference/Extract.mmkin.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
@@ -278,7 +278,7 @@
 #> 
 #> $time
 #>        User      System verstrichen 
-#>       0.179       0.000       0.184 
+#>       0.167       0.000       0.168 
 #> 
 #> $mkinmod
 #> <mkinmod> model generated with
@@ -467,8 +467,8 @@
 #>     }
 #>     return(mC)
 #> }
-#> <bytecode: 0x55555b9b9d58>
-#> <environment: 0x55555be59518>
+#> <bytecode: 0x55555bcec700>
+#> <environment: 0x55555bc44168>
 #> 
 #> $cost_notrans
 #> function (P) 
@@ -490,8 +490,8 @@
 #>         scaleVar = scaleVar)
 #>     return(mC)
 #> }
-#> <bytecode: 0x55555c2673f8>
-#> <environment: 0x55555be59518>
+#> <bytecode: 0x55555c9d13a8>
+#> <environment: 0x55555bc44168>
 #> 
 #> $hessian_notrans
 #>                   parent_0 k_parent_sink
@@ -558,13 +558,13 @@
 #> 99.17407 
 #> 
 #> $date
-#> [1] "Wed Jun  6 01:21:24 2018"
+#> [1] "Wed Jul 18 15:15:52 2018"
 #> 
 #> $version
-#> [1] "0.9.47.1"
+#> [1] "0.9.47.2"
 #> 
 #> $Rversion
-#> [1] "3.5.0"
+#> [1] "3.5.1"
 #> 
 #> attr(,"class")
 #> [1] "mkinfit" "modFit" 
diff --git a/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
index 78caf48d..6888c0ba 100644
--- a/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
+++ b/docs/reference/FOCUS_2006_DFOP_ref_A_to_B.html
@@ -65,7 +65,7 @@ in this fit." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
index c854c11c..624f3908 100644
--- a/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_FOMC_ref_A_to_F.html
@@ -65,7 +65,7 @@ in this fit." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/FOCUS_2006_HS_ref_A_to_F.html b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
index 89ee9ae9..c089e5e7 100644
--- a/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_HS_ref_A_to_F.html
@@ -65,7 +65,7 @@ in this fit." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
index 182c7003..e6846a38 100644
--- a/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
+++ b/docs/reference/FOCUS_2006_SFO_ref_A_to_F.html
@@ -65,7 +65,7 @@ in this fit." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/FOCUS_2006_datasets.html b/docs/reference/FOCUS_2006_datasets.html
index aa84e14b..42ff6926 100644
--- a/docs/reference/FOCUS_2006_datasets.html
+++ b/docs/reference/FOCUS_2006_datasets.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/FOMC.solution.html b/docs/reference/FOMC.solution.html
index 4b8f1c92..9f7db6c1 100644
--- a/docs/reference/FOMC.solution.html
+++ b/docs/reference/FOMC.solution.html
@@ -65,7 +65,7 @@ The form given here differs slightly from the original reference by Gustafson
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/HS.solution.html b/docs/reference/HS.solution.html
index d06a839e..87ee2d20 100644
--- a/docs/reference/HS.solution.html
+++ b/docs/reference/HS.solution.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/IORE.solution.html b/docs/reference/IORE.solution.html
index c037a8d2..18c8a751 100644
--- a/docs/reference/IORE.solution.html
+++ b/docs/reference/IORE.solution.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -178,7 +178,7 @@
 
   print(data.frame(coef(fit.fomc), coef(fit.iore), coef(fit.iore.deS),
                    row.names = paste("model par", 1:3)))
    #>             coef.fit.fomc. coef.fit.iore. coef.fit.iore.deS.
-#> model par 1    85.87489063      85.874891          85.874890
+#> model par 1    85.87489063      85.874890          85.874890
 #> model par 2     0.05192238      -4.826631          -4.826631
 #> model par 3     0.65096665       1.949403           1.949403
      print(rbind(fomc = endpoints(fit.fomc)$distimes, iore = endpoints(fit.iore)$distimes,
               iore.deS = endpoints(fit.iore)$distimes))
    #>              DT50    DT90 DT50back
diff --git a/docs/reference/SFO.solution.html b/docs/reference/SFO.solution.html
index 32ef9f29..ac26f950 100644
--- a/docs/reference/SFO.solution.html
+++ b/docs/reference/SFO.solution.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/SFORB.solution.html b/docs/reference/SFORB.solution.html
index aee32558..bb782104 100644
--- a/docs/reference/SFORB.solution.html
+++ b/docs/reference/SFORB.solution.html
@@ -65,7 +65,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/add_err.html b/docs/reference/add_err.html
index 063234b3..9d71c18c 100644
--- a/docs/reference/add_err.html
+++ b/docs/reference/add_err.html
@@ -63,7 +63,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/endpoints.html b/docs/reference/endpoints.html
index b10998fb..46cb10e1 100644
--- a/docs/reference/endpoints.html
+++ b/docs/reference/endpoints.html
@@ -64,7 +64,7 @@ with the advantage that the SFORB model can also be used for metabolites." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/geometric_mean.html b/docs/reference/geometric_mean.html
index 90b6fd9d..091e65ea 100644
--- a/docs/reference/geometric_mean.html
+++ b/docs/reference/geometric_mean.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/ilr.html b/docs/reference/ilr.html
index 8f337595..34edfc08 100644
--- a/docs/reference/ilr.html
+++ b/docs/reference/ilr.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/index.html b/docs/reference/index.html
index 5785b5aa..d9705ce3 100644
--- a/docs/reference/index.html
+++ b/docs/reference/index.html
@@ -58,7 +58,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -352,9 +352,9 @@
       
         
         
-          
    sigma_rl() 
    
+          
    sigma_twocomp() 
    
         
-        
    Two component error model of Rocke and Lorenzato
    
+        
    Two component error model
    
       
     
       
diff --git a/docs/reference/max_twa_parent.html b/docs/reference/max_twa_parent.html
index 7b3ef8ea..447d9fda 100644
--- a/docs/reference/max_twa_parent.html
+++ b/docs/reference/max_twa_parent.html
@@ -65,7 +65,7 @@ guidance." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mccall81_245T.html b/docs/reference/mccall81_245T.html
index 3326a225..aacdec88 100644
--- a/docs/reference/mccall81_245T.html
+++ b/docs/reference/mccall81_245T.html
@@ -63,7 +63,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -164,10 +164,10 @@
   fit.2 <- mkinfit(SFO_SFO_SFO, subset(mccall81_245T, soil == "Commerce"),
                  parms.ini = c(k_phenol_sink = 0),
                  fixed_parms = "k_phenol_sink", quiet = TRUE)
-  summary(fit.2, data = FALSE)
    #> mkin version used for fitting:    0.9.47.1 
-#> R version used for fitting:       3.5.0 
-#> Date of fit:     Wed Jun  6 01:21:34 2018 
-#> Date of summary: Wed Jun  6 01:21:34 2018 
+  summary(fit.2, data = FALSE)
    #> mkin version used for fitting:    0.9.47.2 
+#> R version used for fitting:       3.5.1 
+#> Date of fit:     Wed Jul 18 15:16:02 2018 
+#> Date of summary: Wed Jul 18 15:16:02 2018 
 #> 
 #> Equations:
 #> d_T245/dt = - k_T245_sink * T245 - k_T245_phenol * T245
@@ -177,7 +177,7 @@
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted with method Port using 246 model solutions performed in 1.452 s
+#> Fitted with method Port using 246 model solutions performed in 1.416 s
 #> 
 #> Weighting: none
 #> 
diff --git a/docs/reference/mkin_long_to_wide.html b/docs/reference/mkin_long_to_wide.html
index 7f4431f5..2bf67d39 100644
--- a/docs/reference/mkin_long_to_wide.html
+++ b/docs/reference/mkin_long_to_wide.html
@@ -63,7 +63,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/mkin_wide_to_long.html b/docs/reference/mkin_wide_to_long.html
index d52f582b..3e0f10f7 100644
--- a/docs/reference/mkin_wide_to_long.html
+++ b/docs/reference/mkin_wide_to_long.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mkinds.html b/docs/reference/mkinds.html
index 43cd51f7..3f4a84ec 100644
--- a/docs/reference/mkinds.html
+++ b/docs/reference/mkinds.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mkinerrmin.html b/docs/reference/mkinerrmin.html
index e6fd8807..44fc1e51 100644
--- a/docs/reference/mkinerrmin.html
+++ b/docs/reference/mkinerrmin.html
@@ -62,7 +62,7 @@ chi-squared test as defined in the FOCUS kinetics report from 2006." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mkinfit.html b/docs/reference/mkinfit.html
index d0b54098..9e59c7e6 100644
--- a/docs/reference/mkinfit.html
+++ b/docs/reference/mkinfit.html
@@ -71,7 +71,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -367,11 +367,14 @@
     reweight.tol or up to the maximum number of iterations
     specified by reweight.max.iter.
     The second reweighting method is called "tc" (two-component error model).
-    When using this method, the two components of the error model according
-    to Rocke and Lorenzato (1995) are estimated from the fit and the resulting
+    When using this method, the two components an error model similar to
+    Rocke and Lorenzato (1995) are estimated from the fit and the resulting
     variances are used for weighting the residuals in each iteration until
     convergence of these components or up to the maximum number of iterations
-    specified.
    
+    specified. Note that this method deviates from the model by Rocke and
+    Lorenzato, as their model implies that the errors follow a lognormal
+    distribution for large values, not a normal distribution as assumed by this
+    method.
    
     
     
       reweight.tol
@@ -427,17 +430,17 @@
     
    Examples
    
     
    # Use shorthand notation for parent only degradation
 fit <- mkinfit("FOMC", FOCUS_2006_C, quiet = TRUE)
-summary(fit)
    #> mkin version used for fitting:    0.9.47.1 
-#> R version used for fitting:       3.5.0 
-#> Date of fit:     Wed Jun  6 01:21:36 2018 
-#> Date of summary: Wed Jun  6 01:21:36 2018 
+summary(fit)
    #> mkin version used for fitting:    0.9.47.2 
+#> R version used for fitting:       3.5.1 
+#> Date of fit:     Wed Jul 18 15:16:04 2018 
+#> Date of summary: Wed Jul 18 15:16:04 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted with method Port using 64 model solutions performed in 0.143 s
+#> Fitted with method Port using 64 model solutions performed in 0.134 s
 #> 
 #> Weighting: none
 #> 
@@ -506,7 +509,7 @@
   m1 = mkinsub("SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults
 print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
                            solution_type = "eigen", quiet = TRUE)))
    #>        User      System verstrichen 
-#>       0.927       0.000       0.929 
    coef(fit)
    #>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
+#>       0.863       0.000       0.864 
    coef(fit)
    #>          parent_0 log_k_parent_sink   log_k_parent_m1     log_k_m1_sink 
 #>          99.59848          -3.03822          -2.98030          -5.24750 
    endpoints(fit)
    #> $ff
 #> parent_sink   parent_m1     m1_sink 
 #>    0.485524    0.514476    1.000000 
diff --git a/docs/reference/mkinmod.html b/docs/reference/mkinmod.html
index 04050367..a9c6bb26 100644
--- a/docs/reference/mkinmod.html
+++ b/docs/reference/mkinmod.html
@@ -66,7 +66,7 @@ For the definition of model types and their parameters, the equations given
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/mkinparplot.html b/docs/reference/mkinparplot.html
index 5a843c0e..33eeefbd 100644
--- a/docs/reference/mkinparplot.html
+++ b/docs/reference/mkinparplot.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mkinplot.html b/docs/reference/mkinplot.html
index 3a55ceae..71437181 100644
--- a/docs/reference/mkinplot.html
+++ b/docs/reference/mkinplot.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mkinpredict.html b/docs/reference/mkinpredict.html
index 946e0dfc..d5357ef6 100644
--- a/docs/reference/mkinpredict.html
+++ b/docs/reference/mkinpredict.html
@@ -63,7 +63,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -321,7 +321,7 @@
                 c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
                 solution_type = "eigen")[201,]))
    #>     time   parent       m1
 #> 201   20 4.978707 27.46227
    #>        User      System verstrichen 
-#>       0.004       0.000       0.004 
      system.time(
+#>       0.003       0.000       0.003 
      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
diff --git a/docs/reference/mkinresplot.html b/docs/reference/mkinresplot.html
index c288bf7c..e73b4905 100644
--- a/docs/reference/mkinresplot.html
+++ b/docs/reference/mkinresplot.html
@@ -64,7 +64,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/mkinsub.html b/docs/reference/mkinsub.html
index 9f98a077..85345135 100644
--- a/docs/reference/mkinsub.html
+++ b/docs/reference/mkinsub.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/mmkin.html b/docs/reference/mmkin.html
index 74b6adad..2a060628 100644
--- a/docs/reference/mmkin.html
+++ b/docs/reference/mmkin.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/plot.mkinfit.html b/docs/reference/plot.mkinfit.html
index 525a8453..07fc4854 100644
--- a/docs/reference/plot.mkinfit.html
+++ b/docs/reference/plot.mkinfit.html
@@ -66,7 +66,7 @@ If the current plot device is a tikz device,
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/plot.mmkin.html b/docs/reference/plot.mmkin.html
index a554a489..829105bd 100644
--- a/docs/reference/plot.mmkin.html
+++ b/docs/reference/plot.mmkin.html
@@ -65,7 +65,7 @@ If the current plot device is a tikz device,
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/print.mkinds.html b/docs/reference/print.mkinds.html
index ade048f0..70c4f768 100644
--- a/docs/reference/print.mkinds.html
+++ b/docs/reference/print.mkinds.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/print.mkinmod.html b/docs/reference/print.mkinmod.html
index 64d3a03c..141dd1c9 100644
--- a/docs/reference/print.mkinmod.html
+++ b/docs/reference/print.mkinmod.html
@@ -61,7 +61,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/schaefer07_complex_case.html b/docs/reference/schaefer07_complex_case.html
index 06b3c049..18f3b78f 100644
--- a/docs/reference/schaefer07_complex_case.html
+++ b/docs/reference/schaefer07_complex_case.html
@@ -63,7 +63,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/sigma_rl.html b/docs/reference/sigma_rl.html
index bb9fd396..c8fc3bf9 100644
--- a/docs/reference/sigma_rl.html
+++ b/docs/reference/sigma_rl.html
@@ -63,7 +63,7 @@ $$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$" />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
diff --git a/docs/reference/sigma_twocomp.html b/docs/reference/sigma_twocomp.html
new file mode 100644
index 00000000..8bf1d5f6
--- /dev/null
+++ b/docs/reference/sigma_twocomp.html
@@ -0,0 +1,203 @@
+
+
+
+  
+  
+
+
+
+Two component error model — sigma_twocomp • mkin
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+  
+
+  
+    
    
+      
    
+      
+
+      
+      
    
+
+
    
+  
    
+    
    
+    
    Two component error model
    
+    
+    
+    
    
+
+    
    
+    
+    
    Function describing the standard deviation of the measurement error 
+  in dependence of the measured value \(y\):
    
+
    $$\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}$$
    
+
    This is the error model used for example by Werner et al. (1978). The model
+  proposed by Rocke and Lorenzato (1995) can be written in this form as well,
+  but assumes approximate lognormal distribution of errors for high values of y.
    
+    
+    
    
+
+    
    sigma_twocomp(y, sigma_low, rsd_high)
    
+    
+    
    Arguments
    
+    
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
    y
    The magnitude of the observed value
    sigma_low
    The asymptotic minimum of the standard deviation for low observed values
    rsd_high
    The coefficient describing the increase of the standard deviation with 
+    the magnitude of the observed value
    
+    
+    
    Value
    
+
+    
    The standard deviation of the response variable.
    
+    
+    
    References
    
+
+    
    Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
+  Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry
+  24(11), 1895-1898.
    
+
    Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for
+  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
    
+    
+
+  
    
+  
+
    
+
+      
    
+      
    
+  
    Developed by Johannes Ranke.
    
+
    
+
+
    
+  
    Site built with pkgdown.
    
+
    
+
+      
    
+   
    
+
+  
+
+  
+
+
diff --git a/docs/reference/summary.mkinfit.html b/docs/reference/summary.mkinfit.html
index c8919f1c..4d9c511c 100644
--- a/docs/reference/summary.mkinfit.html
+++ b/docs/reference/summary.mkinfit.html
@@ -64,7 +64,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -204,17 +204,17 @@
     
 
     
    Examples
    
-    
      summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE))
    #> mkin version used for fitting:    0.9.47.1 
-#> R version used for fitting:       3.5.0 
-#> Date of fit:     Wed Jun  6 01:21:46 2018 
-#> Date of summary: Wed Jun  6 01:21:46 2018 
+    
      summary(mkinfit(mkinmod(parent = mkinsub("SFO")), FOCUS_2006_A, quiet = TRUE))
    #> mkin version used for fitting:    0.9.47.2 
+#> R version used for fitting:       3.5.1 
+#> Date of fit:     Wed Jul 18 15:16:13 2018 
+#> Date of summary: Wed Jul 18 15:16:13 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent_sink * parent
 #> 
 #> Model predictions using solution type analytical 
 #> 
-#> Fitted with method Port using 35 model solutions performed in 0.075 s
+#> Fitted with method Port using 35 model solutions performed in 0.073 s
 #> 
 #> Weighting: none
 #> 
diff --git a/docs/reference/synthetic_data_for_UBA.html b/docs/reference/synthetic_data_for_UBA.html
index 6e0ac227..9d9404e5 100644
--- a/docs/reference/synthetic_data_for_UBA.html
+++ b/docs/reference/synthetic_data_for_UBA.html
@@ -39,7 +39,10 @@ Variance component 'a' is based on a normal distribution with standard deviation
  Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
  Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
  minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y.
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the 
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.
 Initial concentrations for metabolites and all values where adding the variance component resulted
  in a value below the assumed limit of detection of 0.1 were set to NA.
 As an example, the first dataset has the title SFO_lin_a and is based on the SFO model
@@ -73,7 +76,7 @@ Compare also the code in the example section to see the degradation models." />
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
@@ -142,7 +145,10 @@ Compare also the code in the example section to see the degradation models." />
  Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
  Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
  minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y.
    
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the 
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.
    
 
    Initial concentrations for metabolites and all values where adding the variance component resulted
  in a value below the assumed limit of detection of 0.1 were set to NA.
    
 
    As an example, the first dataset has the title SFO_lin_a and is based on the SFO model
diff --git a/docs/reference/test_data_from_UBA_2014.html b/docs/reference/test_data_from_UBA_2014.html
index 090b0c22..5b683283 100644
--- a/docs/reference/test_data_from_UBA_2014.html
+++ b/docs/reference/test_data_from_UBA_2014.html
@@ -62,7 +62,7 @@
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
    
 
diff --git a/docs/reference/transform_odeparms.html b/docs/reference/transform_odeparms.html
index 3adb3a10..a2f7a338 100644
--- a/docs/reference/transform_odeparms.html
+++ b/docs/reference/transform_odeparms.html
@@ -69,7 +69,7 @@ The transformation of sets of formation fractions is fragile, as it supposes
       
       
         mkin
-        0.9.47.1
+        0.9.47.2
       
     
 
@@ -198,10 +198,10 @@ The transformation of sets of formation fractions is fragile, as it supposes
   parent = list(type = "SFO", to = "m1", sink = TRUE),
   m1 = list(type = "SFO"))
    #> Successfully compiled differential equation model from auto-generated C code.
    # Fit the model to the FOCUS example dataset D using defaults
 fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
-summary(fit, data=FALSE) # See transformed and backtransformed parameters
    #> mkin version used for fitting:    0.9.47.1 
-#> R version used for fitting:       3.5.0 
-#> Date of fit:     Wed Jun  6 01:21:47 2018 
-#> Date of summary: Wed Jun  6 01:21:47 2018 
+summary(fit, data=FALSE) # See transformed and backtransformed parameters
    #> mkin version used for fitting:    0.9.47.2 
+#> R version used for fitting:       3.5.1 
+#> Date of fit:     Wed Jul 18 15:16:15 2018 
+#> Date of summary: Wed Jul 18 15:16:15 2018 
 #> 
 #> Equations:
 #> d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -209,7 +209,7 @@ The transformation of sets of formation fractions is fragile, as it supposes
 #> 
 #> Model predictions using solution type deSolve 
 #> 
-#> Fitted with method Port using 153 model solutions performed in 0.628 s
+#> Fitted with method Port using 153 model solutions performed in 0.639 s
 #> 
 #> Weighting: none
 #> 
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd
index 32edb28b..0f06b321 100644
--- a/man/mkinfit.Rd
+++ b/man/mkinfit.Rd
@@ -212,11 +212,14 @@ mkinfit(mkinmod, observed,
     \code{reweight.tol} or up to the maximum number of iterations
     specified by \code{reweight.max.iter}.
     The second reweighting method is called "tc" (two-component error model).
-    When using this method, the two components of the error model according
-    to Rocke and Lorenzato (1995) are estimated from the fit and the resulting
+    When using this method, the two components an error model similar to
+    Rocke and Lorenzato (1995) are estimated from the fit and the resulting
     variances are used for weighting the residuals in each iteration until
     convergence of these components or up to the maximum number of iterations
-    specified.
+    specified. Note that this method deviates from the model by Rocke and
+    Lorenzato, as their model implies that the errors follow a lognormal
+    distribution for large values, not a normal distribution as assumed by this
+    method.
   }
   \item{reweight.tol}{
     Tolerance for convergence criterion for the variance components
diff --git a/man/sigma_rl.Rd b/man/sigma_rl.Rd
deleted file mode 100644
index 0b5d6f3c..00000000
--- a/man/sigma_rl.Rd
+++ /dev/null
@@ -1,26 +0,0 @@
-\name{sigma_rl}
-\alias{sigma_rl}
-\title{ Two component error model of Rocke and Lorenzato}
-\description{
-  Function describing the standard deviation of the measurement error 
-  in dependence of the measured value \eqn{y}:
-
-    \deqn{\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}}{%
-      sigma = sqrt(sigma_low^2 + y^2 * rsd_high^2)}
-}
-\usage{
-sigma_rl(y, sigma_low, rsd_high)
-}
-\arguments{
-  \item{y}{ The magnitude of the observed value } 
-  \item{sigma_low}{ The asymptotic minimum of the standard deviation for low observed values }
-  \item{rsd_high}{ The coefficient describing the increase of the standard deviation with 
-    the magnitude of the observed value }
-}
-\value{
-  The standard deviation of the response variable.
-}
-\references{
-  Rocke, David M. und Lorenzato, Stefan (1995) A two-component model for
-  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
-}
diff --git a/man/sigma_twocomp.Rd b/man/sigma_twocomp.Rd
new file mode 100644
index 00000000..6f941093
--- /dev/null
+++ b/man/sigma_twocomp.Rd
@@ -0,0 +1,34 @@
+\name{sigma_twocomp}
+\alias{sigma_twocomp}
+\title{Two component error model}
+\description{
+  Function describing the standard deviation of the measurement error 
+  in dependence of the measured value \eqn{y}:
+
+    \deqn{\sigma = \sqrt{ \sigma_{low}^2 + y^2 * {rsd}_{high}^2}}{%
+      sigma = sqrt(sigma_low^2 + y^2 * rsd_high^2)}
+
+  This is the error model used for example by Werner et al. (1978). The model
+  proposed by Rocke and Lorenzato (1995) can be written in this form as well,
+  but assumes approximate lognormal distribution of errors for high values of y.
+}
+\usage{
+sigma_twocomp(y, sigma_low, rsd_high)
+}
+\arguments{
+  \item{y}{ The magnitude of the observed value } 
+  \item{sigma_low}{ The asymptotic minimum of the standard deviation for low observed values }
+  \item{rsd_high}{ The coefficient describing the increase of the standard deviation with 
+    the magnitude of the observed value }
+}
+\value{
+  The standard deviation of the response variable.
+}
+\references{
+  Werner, Mario, Brooks, Samuel H., and Knott, Lancaster B. (1978)
+  Additive, Multiplicative, and Mixed Analytical Errors. Clinical Chemistry
+  24(11), 1895-1898.
+
+  Rocke, David M. and Lorenzato, Stefan (1995) A two-component model for
+  measurement error in analytical chemistry. Technometrics 37(2), 176-184.
+}
diff --git a/man/synthetic_data_for_UBA.Rd b/man/synthetic_data_for_UBA.Rd
index a9df9767..f9d3c77b 100644
--- a/man/synthetic_data_for_UBA.Rd
+++ b/man/synthetic_data_for_UBA.Rd
@@ -13,7 +13,10 @@
  Variance component 'b' is also based on a normal distribution, but with a standard deviation of 7.
  Variance component 'c' is based on the error model from Rocke and Lorenzato (1995), with the
  minimum standard deviation (for small y values) of 0.5, and a proportionality constant of 0.07
- for the increase of the standard deviation with y.
+ for the increase of the standard deviation with y. Note that this is a simplified version
+ of the error model proposed by Rocke and Lorenzato (1995), as in their model the error of the 
+ measured values approximates lognormal distribution for high values, whereas we are using
+ normally distributed error components all along.
 
  Initial concentrations for metabolites and all values where adding the variance component resulted
  in a value below the assumed limit of detection of 0.1 were set to \code{NA}.
diff --git a/vignettes/FOCUS_D.html b/vignettes/FOCUS_D.html
index 84e3748c..bfbe2f7e 100644
--- a/vignettes/FOCUS_D.html
+++ b/vignettes/FOCUS_D.html
@@ -12,7 +12,7 @@
 
 
 
-
+
 
 Example evaluation of FOCUS Example Dataset D
 
@@ -70,13 +70,13 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
 
 
    Example evaluation of FOCUS Example Dataset D
    
 
    Johannes Ranke
    
-
    2018-01-14
    
+
    2018-07-17
    
 
 
 
 
    This is just a very simple vignette showing how to fit a degradation model for a parent compound with one transformation product using mkin. After loading the library we look a the data. We have observed concentrations in the column named value at the times specified in column time for the two observed variables named parent and m1.
    
 
    library("mkin", quietly = TRUE)
-print(FOCUS_2006_D)
    
+print(FOCUS_2006_D)
    
 
    ##      name time  value
 ## 1  parent    0  99.46
 ## 2  parent    0 102.04
@@ -126,13 +126,13 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
 
    The call to mkinmod returns a degradation model. The differential equations represented in R code can be found in the character vector $diffs of the mkinmod object. If a C compiler (gcc) is installed and functional, the differential equation model will be compiled from auto-generated C code.
    
 
    SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO"))
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
-
    print(SFO_SFO$diffs)
    
+
    print(SFO_SFO$diffs)
    
 
    ##                                                       parent 
 ## "d_parent = - k_parent_sink * parent - k_parent_m1 * parent" 
 ##                                                           m1 
 ##             "d_m1 = + k_parent_m1 * parent - k_m1_sink * m1"
    
 
    We do the fitting without progress report (quiet = TRUE).
    
-
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
    
+
    fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE)
    
 
    A plot of the fit including a residual plot for both observed variables is obtained using the plot_sep method for mkinfit objects, which shows separate graphs for all compounds and their residuals.
    
 
    plot_sep(fit, lpos = c("topright", "bottomright"))
    
 
    
@@ -141,10 +141,10 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
 
    
 
    A comprehensive report of the results is obtained using the summary method for mkinfit objects.
    
 
    summary(fit)
    
-
    ## mkin version:    0.9.47.1 
-## R version:       3.4.3 
-## Date of fit:     Sun Jan 14 17:50:03 2018 
-## Date of summary: Sun Jan 14 17:50:03 2018 
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:19 2018 
+## Date of summary: Tue Jul 17 15:54:19 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent - k_parent_m1 * parent
@@ -152,7 +152,7 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
 ## 
 ## Model predictions using solution type deSolve 
 ## 
-## Fitted with method Port using 153 model solutions performed in 1.072 s
+## Fitted with method Port using 153 model solutions performed in 0.658 s
 ## 
 ## Weighting: none
 ## 
@@ -219,50 +219,46 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
 ## 
 ## 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 -7.382e-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
    
+##     0   parent    99.46  99.59848 -1.385e-01
+##     0   parent   102.04  99.59848  2.442e+00
+##     1   parent    93.50  90.23787  3.262e+00
+##     1   parent    92.50  90.23787  2.262e+00
+##     3   parent    63.23  74.07320 -1.084e+01
+##     3   parent    68.99  74.07320 -5.083e+00
+##     7   parent    52.32  49.91207  2.408e+00
+##     7   parent    55.13  49.91207  5.218e+00
+##    14   parent    27.27  25.01257  2.257e+00
+##    14   parent    26.64  25.01257  1.627e+00
+##    21   parent    11.50  12.53462 -1.035e+00
+##    21   parent    11.64  12.53462 -8.946e-01
+##    35   parent     2.85   3.14787 -2.979e-01
+##    35   parent     2.91   3.14787 -2.379e-01
+##    50   parent     0.69   0.71624 -2.624e-02
+##    50   parent     0.63   0.71624 -8.624e-02
+##    75   parent     0.05   0.06074 -1.074e-02
+##    75   parent     0.06   0.06074 -7.382e-04
+##     0       m1     0.00   0.00000  0.000e+00
+##     0       m1     0.00   0.00000  0.000e+00
+##     1       m1     4.84   4.80296  3.704e-02
+##     1       m1     5.64   4.80296  8.370e-01
+##     3       m1    12.91  13.02400 -1.140e-01
+##     3       m1    12.96  13.02400 -6.400e-02
+##     7       m1    22.97  25.04476 -2.075e+00
+##     7       m1    24.47  25.04476 -5.748e-01
+##    14       m1    41.69  36.69002  5.000e+00
+##    14       m1    33.21  36.69002 -3.480e+00
+##    21       m1    44.37  41.65310  2.717e+00
+##    21       m1    46.44  41.65310  4.787e+00
+##    35       m1    41.22  43.31312 -2.093e+00
+##    35       m1    37.95  43.31312 -5.363e+00
+##    50       m1    41.19  41.21831 -2.831e-02
+##    50       m1    40.01  41.21831 -1.208e+00
+##    75       m1    40.09  36.44704  3.643e+00
+##    75       m1    33.85  36.44704 -2.597e+00
+##   100       m1    31.04  31.98163 -9.416e-01
+##   100       m1    33.13  31.98163  1.148e+00
+##   120       m1    25.15  28.78984 -3.640e+00
+##   120       m1    33.31  28.78984  4.520e+00
    
 
 
 
diff --git a/vignettes/FOCUS_L.html b/vignettes/FOCUS_L.html
index 9bdfb5c6..b26a9e43 100644
--- a/vignettes/FOCUS_L.html
+++ b/vignettes/FOCUS_L.html
@@ -1,248 +1,260 @@
 
-
+
+
+
 
-
 
-Laboratory Data L1
+
+
+
 
-
 
-
-
+
 
-
-
+
 
-
-
+Example evaluation of FOCUS Laboratory Data L1 to L3
 
+
+
+
+
+
+
+
+
+
+
+
+
 
+
 
+
 
-body {
-  max-width: 800px;
-  margin: auto;
-  padding: 1em;
-  line-height: 20px;
-}
 
-tt, code, pre {
-   font-family: 'DejaVu Sans Mono', 'Droid Sans Mono', 'Lucida Console', Consolas, Monaco, monospace;
-}
 
+
+
+
+
+
+
 
-a:visited {
-   color: rgb(50%, 0%, 50%);
+
+
+
 
-pre, img {
-  max-width: 100%;
+
    
+
+
+
+
+
+
+
+
+
+
+
+
 
+
+
    
+
    
+
    
+
    
+
    
 
+
    
 
-
 
-
-
    Laboratory Data L1
    
 
-
    The following code defines example dataset L1 from the FOCUS kinetics
-report, p. 284:
    
 
-
    library("mkin", quietly = TRUE)
+
+
+
+
    
+
    Laboratory Data L1
    
+
    The following code defines example dataset L1 from the FOCUS kinetics report, p. 284:
    
+
    library("mkin", quietly = TRUE)
 FOCUS_2006_L1 = data.frame(
   t = rep(c(0, 1, 2, 3, 5, 7, 14, 21, 30), each = 2),
   parent = c(88.3, 91.4, 85.6, 84.5, 78.9, 77.6,
              72.0, 71.9, 50.3, 59.4, 47.0, 45.1,
              27.7, 27.3, 10.0, 10.4, 2.9, 4.0))
-FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
-
    
-
-
    Here we use the assumptions of simple first order (SFO), the case of declining
-rate constant over time (FOMC) and the case of two different phases of the
-kinetics (DFOP). For a more detailed discussion of the models, please see the
-FOCUS kinetics report.
    
-
-
    Since mkin version 0.9-32 (July 2014), we can use shorthand notation like "SFO"
-for parent only degradation models. The following two lines fit the model and
-produce the summary report of the model fit. This covers the numerical analysis
-given in the FOCUS report.
    
-
-
    m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
-summary(m.L1.SFO)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:54 2018 
-## Date of summary: Thu Mar  1 14:24:54 2018 
+FOCUS_2006_L1_mkin <- mkin_wide_to_long(FOCUS_2006_L1)
    
+
    Here we use the assumptions of simple first order (SFO), the case of declining rate constant over time (FOMC) and the case of two different phases of the kinetics (DFOP). For a more detailed discussion of the models, please see the FOCUS kinetics report.
    
+
    Since mkin version 0.9-32 (July 2014), we can use shorthand notation like "SFO" for parent only degradation models. The following two lines fit the model and produce the summary report of the model fit. This covers the numerical analysis given in the FOCUS report.
    
+
    m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
+summary(m.L1.SFO)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:20 2018 
+## Date of summary: Tue Jul 17 15:54:20 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.24 s
+## Fitted with method Port using 37 model solutions performed in 0.097 s
 ## 
 ## Weighting: none
 ## 
@@ -311,46 +323,29 @@ summary(m.L1.SFO)
 ##    21   parent     10.0    12.416  -2.4163
 ##    21   parent     10.4    12.416  -2.0163
 ##    30   parent      2.9     5.251  -2.3513
-##    30   parent      4.0     5.251  -1.2513
-
    
-
+##    30   parent      4.0     5.251  -1.2513
    
 
    A plot of the fit is obtained with the plot function for mkinfit objects.
    
-
-
    plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
-
    
-
-
    plot of chunk unnamed-chunk-4
    
-
+
    plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
    
+
    
 
    The residual plot can be easily obtained by
    
-
-
    mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
-
    
-
-
    plot of chunk unnamed-chunk-5
    
-
-
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level
-is checked.
    
-
-
    m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
-plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
-
    
-
-
    plot of chunk unnamed-chunk-6
    
-
-
    summary(m.L1.FOMC, data = FALSE)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:56 2018 
-## Date of summary: Thu Mar  1 14:24:57 2018 
+
    mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
    
+
    
+
    For comparison, the FOMC model is fitted as well, and the χ2 error level is checked.
    
+
    m.L1.FOMC <- mkinfit("FOMC", FOCUS_2006_L1_mkin, quiet=TRUE)
+plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
    
+
    
+
    summary(m.L1.FOMC, data = FALSE)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:22 2018 
+## Date of summary: Tue Jul 17 15:54:22 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - (alpha/beta) * 1/((time/beta) + 1) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 611 model solutions performed in 1.376 s
+## Fitted with method Port using 611 model solutions performed in 1.446 s
 ## 
 ## Weighting: none
 ## 
@@ -399,100 +394,50 @@ plot(m.L1.FOMC, show_errmin = TRUE, main = "FOCUS L1 - FOMC")
 ## 
 ## Estimated disappearance times:
 ##         DT50  DT90 DT50back
-## parent 7.249 24.08    7.249
-
    
-
-
    We get a warning that the default optimisation algorithm Port did not converge, which
-is an indication that the model is overparameterised, i.e. contains too many
-parameters that are ill-defined as a consequence.
    
-
-
    And in fact, due to the higher number of parameters, and the lower number of
-degrees of freedom of the fit, the \(\chi^2\) error level is actually higher for
-the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the
-parameters log_alpha and log_beta internally fitted in the model have
-excessive confidence intervals, that span more than 25 orders of magnitude (!)
-when backtransformed to the scale of alpha and beta. Also, the t-test
-for significant difference from zero does not indicate such a significant difference,
-with p-values greater than 0.1, and finally, the parameter correlation of log_alpha
-and log_beta is 1.000, clearly indicating that the model is overparameterised.
    
-
-
    The \(\chi^2\) error levels reported in Appendix 3 and Appendix 7 to the FOCUS
-kinetics report are rounded to integer percentages and partly deviate by one
-percentage point from the results calculated by mkin. The reason for
-this is not known. However, mkin gives the same \(\chi^2\) error levels
-as the kinfit package and the calculation routines of the kinfit package have
-been extensively compared to the results obtained by the KinGUI
-software, as documented in the kinfit package vignette. KinGUI was the first
-widely used standard package in this field. Also, the calculation of
-\(\chi^2\) error levels was compared with KinGUII, CAKE and DegKin manager in
-a project sponsored by the German Umweltbundesamt [@ranke2014].
    
-
+## parent 7.249 24.08    7.249
    
+
    We get a warning that the default optimisation algorithm Port did not converge, which is an indication that the model is overparameterised, i.e. contains too many parameters that are ill-defined as a consequence.
    
+
    And in fact, due to the higher number of parameters, and the lower number of degrees of freedom of the fit, the χ2 error level is actually higher for the FOMC model (3.6%) than for the SFO model (3.4%). Additionally, the parameters log_alpha and log_beta internally fitted in the model have excessive confidence intervals, that span more than 25 orders of magnitude (!) when backtransformed to the scale of alpha and beta. Also, the t-test for significant difference from zero does not indicate such a significant difference, with p-values greater than 0.1, and finally, the parameter correlation of log_alpha and log_beta is 1.000, clearly indicating that the model is overparameterised.
    
+
    The χ2 error levels reported in Appendix 3 and Appendix 7 to the FOCUS kinetics report are rounded to integer percentages and partly deviate by one percentage point from the results calculated by mkin. The reason for this is not known. However, mkin gives the same χ2 error levels as the kinfit package and the calculation routines of the kinfit package have been extensively compared to the results obtained by the KinGUI software, as documented in the kinfit package vignette. KinGUI was the first widely used standard package in this field. Also, the calculation of χ2 error levels was compared with KinGUII, CAKE and DegKin manager in a project sponsored by the German Umweltbundesamt (Ranke 2014).
    
+
    
+
    
 
    Laboratory Data L2
    
-
-
    The following code defines example dataset L2 from the FOCUS kinetics
-report, p. 287:
    
-
-
    FOCUS_2006_L2 = data.frame(
+
    The following code defines example dataset L2 from the FOCUS kinetics report, p. 287:
    
+
    FOCUS_2006_L2 = data.frame(
   t = rep(c(0, 1, 3, 7, 14, 28), each = 2),
   parent = c(96.1, 91.8, 41.4, 38.7,
              19.3, 22.3, 4.6, 4.6,
              2.6, 1.2, 0.3, 0.6))
-FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
-
    
-
+FOCUS_2006_L2_mkin <- mkin_wide_to_long(FOCUS_2006_L2)
    
+
    
 
    SFO fit for L2
    
-
-
    Again, the SFO model is fitted and the result is plotted. The residual plot
-can be obtained simply by adding the argument show_residuals to the plot
-command.
    
-
-
    m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
+
    Again, the SFO model is fitted and the result is plotted. The residual plot can be obtained simply by adding the argument show_residuals to the plot command.
    
+
    m.L2.SFO <- mkinfit("SFO", FOCUS_2006_L2_mkin, quiet=TRUE)
 plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - SFO")
-
    
-
-
    plot of chunk unnamed-chunk-8
    
-
-
    The \(\chi^2\) error level of 14% suggests that the model does not fit very well.
-This is also obvious from the plots of the fit, in which we have included
-the residual plot.
    
-
-
    In the FOCUS kinetics report, it is stated that there is no apparent systematic
-error observed from the residual plot up to the measured DT90 (approximately at
-day 5), and there is an underestimation beyond that point.
    
-
-
    We may add that it is difficult to judge the random nature of the residuals just
-from the three samplings at days 0, 1 and 3. Also, it is not clear a
-priori why a consistent underestimation after the approximate DT90 should be
-irrelevant. However, this can be rationalised by the fact that the FOCUS fate
-models generally only implement SFO kinetics.
    
-
+     main = "FOCUS L2 - SFO")
    
+
    
+
    The χ2 error level of 14% suggests that the model does not fit very well. This is also obvious from the plots of the fit, in which we have included the residual plot.
    
+
    In the FOCUS kinetics report, it is stated that there is no apparent systematic error observed from the residual plot up to the measured DT90 (approximately at day 5), and there is an underestimation beyond that point.
    
+
    We may add that it is difficult to judge the random nature of the residuals just from the three samplings at days 0, 1 and 3. Also, it is not clear a priori why a consistent underestimation after the approximate DT90 should be irrelevant. However, this can be rationalised by the fact that the FOCUS fate models generally only implement SFO kinetics.
    
+
    
+
    
 
    FOMC fit for L2
    
-
-
    For comparison, the FOMC model is fitted as well, and the \(\chi^2\) error level
-is checked.
    
-
-
    m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
+
    For comparison, the FOMC model is fitted as well, and the χ2 error level is checked.
    
+
    m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.FOMC, show_residuals = TRUE,
-     main = "FOCUS L2 - FOMC")
-
    
-
-
    plot of chunk unnamed-chunk-9
    
-
-
    summary(m.L2.FOMC, data = FALSE)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:57 2018 
-## Date of summary: Thu Mar  1 14:24:57 2018 
+     main = "FOCUS L2 - FOMC")
    
+
    
+
    summary(m.L2.FOMC, data = FALSE)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:23 2018 
+## Date of summary: Tue Jul 17 15:54:23 2018 
 ## 
 ## 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 0.169 s
+## Fitted with method Port using 81 model solutions performed in 0.189 s
 ## 
 ## Weighting: none
 ## 
@@ -541,31 +486,21 @@ plot(m.L2.FOMC, show_residuals = TRUE,
 ## 
 ## Estimated disappearance times:
 ##          DT50  DT90 DT50back
-## parent 0.8092 5.356    1.612
-
    
-
-
    The error level at which the \(\chi^2\) test passes is much lower in this case.
-Therefore, the FOMC model provides a better description of the data, as less
-experimental error has to be assumed in order to explain the data.
    
-
+## parent 0.8092 5.356    1.612
    
+
    The error level at which the χ2 test passes is much lower in this case. Therefore, the FOMC model provides a better description of the data, as less experimental error has to be assumed in order to explain the data.
    
+
    
+
    
 
    DFOP fit for L2
    
-
-
    Fitting the four parameter DFOP model further reduces the \(\chi^2\) error level.
    
-
-
    m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
+
    Fitting the four parameter DFOP model further reduces the χ2 error level.
    
+
    m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
-     main = "FOCUS L2 - DFOP")
-
    
-
-
    plot of chunk unnamed-chunk-10
    
-
-
    summary(m.L2.DFOP, data = FALSE)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:58 2018 
-## Date of summary: Thu Mar  1 14:24:58 2018 
+     main = "FOCUS L2 - DFOP")
    
+
    
+
    summary(m.L2.DFOP, data = FALSE)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:23 2018 
+## Date of summary: Tue Jul 17 15:54:23 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -574,7 +509,7 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 336 model solutions performed in 0.721 s
+## Fitted with method Port using 336 model solutions performed in 0.802 s
 ## 
 ## Weighting: none
 ## 
@@ -602,12 +537,8 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## log_k2    -1.0880         NA    NA    NA
 ## g_ilr     -0.2821         NA    NA    NA
 ## 
-## Parameter correlation:
-
    
-
-
    ## Warning in print.summary.mkinfit(x): Could not estimate covariance matrix; singular system:
-
    
-
+## Parameter correlation:
    
+
    ## Warning in print.summary.mkinfit(x): Could not estimate covariance matrix; singular system:
    
 
    ## Could not estimate covariance matrix; singular system:
 ## 
 ## Residual standard error: 1.732 on 8 degrees of freedom
@@ -629,62 +560,36 @@ plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
 ## 
 ## Estimated disappearance times:
 ##          DT50  DT90 DT50_k1 DT50_k2
-## parent 0.5335 5.311 0.03009   2.058
-
    
-
-
    Here, the DFOP model is clearly the best-fit model for dataset L2 based on the
-chi2 error level criterion. However, the failure to calculate the covariance
-matrix indicates that the parameter estimates correlate excessively. Therefore,
-the FOMC model may be preferred for this dataset.
    
-
+## parent 0.5335 5.311 0.03009   2.058
    
+
    Here, the DFOP model is clearly the best-fit model for dataset L2 based on the chi^2 error level criterion. However, the failure to calculate the covariance matrix indicates that the parameter estimates correlate excessively. Therefore, the FOMC model may be preferred for this dataset.
    
+
+
+
    
 
    Laboratory Data L3
    
-
-
    The following code defines example dataset L3 from the FOCUS kinetics report,
-p. 290.
    
-
-
    FOCUS_2006_L3 = data.frame(
+
    The following code defines example dataset L3 from the FOCUS kinetics report, p. 290.
    
+
    FOCUS_2006_L3 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(97.8, 60, 51, 43, 35, 22, 15, 12))
-FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
-
    
-
+FOCUS_2006_L3_mkin <- mkin_wide_to_long(FOCUS_2006_L3)
    
+
    
 
    Fit multiple models
    
-
-
    As of mkin version 0.9-39 (June 2015), we can fit several models to
-one or more datasets in one call to the function mmkin. The datasets
-have to be passed in a list, in this case a named list holding only
-the L3 dataset prepared above.
    
-
-
    # Only use one core here, not to offend the CRAN checks
+
    As of mkin version 0.9-39 (June 2015), we can fit several models to one or more datasets in one call to the function mmkin. The datasets have to be passed in a list, in this case a named list holding only the L3 dataset prepared above.
    
+
    # Only use one core here, not to offend the CRAN checks
 mm.L3 <- mmkin(c("SFO", "FOMC", "DFOP"), cores = 1,
                list("FOCUS L3" = FOCUS_2006_L3_mkin), quiet = TRUE)
-plot(mm.L3)
-
    
-
-
    plot of chunk unnamed-chunk-12
    
-
-
    The \(\chi^2\) error level of 21% as well as the plot suggest that the SFO model
-does not fit very well.  The FOMC model performs better, with an
-error level at which the \(\chi^2\) test passes of 7%.  Fitting the four
-parameter DFOP model further reduces the \(\chi^2\) error level
-considerably.
    
-
+plot(mm.L3)
    
+
    
+
    The χ2 error level of 21% as well as the plot suggest that the SFO model does not fit very well. The FOMC model performs better, with an error level at which the χ2 test passes of 7%. Fitting the four parameter DFOP model further reduces the χ2 error level considerably.
    
+
    
+
    
 
    Accessing mmkin objects
    
-
-
    The objects returned by mmkin are arranged like a matrix, with
-models as a row index and datasets as a column index.
    
-
-
    We can extract the summary and plot for e.g. the DFOP fit,
-using square brackets for indexing which will result in the use of
-the summary and plot functions working on mkinfit objects.
    
-
-
    summary(mm.L3[["DFOP", 1]])
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:59 2018 
-## Date of summary: Thu Mar  1 14:24:59 2018 
+
    The objects returned by mmkin are arranged like a matrix, with models as a row index and datasets as a column index.
    
+
    We can extract the summary and plot for e.g. the DFOP fit, using square brackets for indexing which will result in the use of the summary and plot functions working on mkinfit objects.
    
+
    summary(mm.L3[["DFOP", 1]])
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:24 2018 
+## Date of summary: Tue Jul 17 15:54:24 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
@@ -693,7 +598,7 @@ the summary and plot functions working on mkinfit objects.
    
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 137 model solutions performed in 0.283 s
+## Fitted with method Port using 137 model solutions performed in 0.318 s
 ## 
 ## Weighting: none
 ## 
@@ -758,64 +663,40 @@ the summary and plot functions working on mkinfit objects.
    
 ##    30   parent     35.0     35.15 -0.14707
 ##    60   parent     22.0     23.26 -1.25919
 ##    91   parent     15.0     15.18 -0.18181
-##   120   parent     12.0     10.19  1.81395
-
    
-
-
    plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
-
    
-
-
    plot of chunk unnamed-chunk-13
    
-
-
    Here, a look to the model plot, the confidence intervals of the parameters
-and the correlation matrix suggest that the parameter estimates are reliable, and
-the DFOP model can be used as the best-fit model based on the \(\chi^2\) error
-level criterion for laboratory data L3.
    
-
-
    This is also an example where the standard t-test for the parameter g_ilr is
-misleading, as it tests for a significant difference from zero. In this case,
-zero appears to be the correct value for this parameter, and the confidence
-interval for the backtransformed parameter g is quite narrow.
    
-
+##   120   parent     12.0     10.19  1.81395
    
+
    plot(mm.L3[["DFOP", 1]], show_errmin = TRUE)
    
+
    
+
    Here, a look to the model plot, the confidence intervals of the parameters and the correlation matrix suggest that the parameter estimates are reliable, and the DFOP model can be used as the best-fit model based on the χ2 error level criterion for laboratory data L3.
    
+
    This is also an example where the standard t-test for the parameter g_ilr is misleading, as it tests for a significant difference from zero. In this case, zero appears to be the correct value for this parameter, and the confidence interval for the backtransformed parameter g is quite narrow.
    
+
    
+
    
+
    
 
    Laboratory Data L4
    
-
-
    The following code defines example dataset L4 from the FOCUS kinetics
-report, p. 293:
    
-
-
    FOCUS_2006_L4 = data.frame(
+
    The following code defines example dataset L4 from the FOCUS kinetics report, p. 293:
    
+
    FOCUS_2006_L4 = data.frame(
   t = c(0, 3, 7, 14, 30, 60, 91, 120),
   parent = c(96.6, 96.3, 94.3, 88.8, 74.9, 59.9, 53.5, 49.0))
-FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
-
    
-
+FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
    
 
    Fits of the SFO and FOMC models, plots and summaries are produced below:
    
-
-
    # Only use one core here, not to offend the CRAN checks
+
    # Only use one core here, not to offend the CRAN checks
 mm.L4 <- mmkin(c("SFO", "FOMC"), cores = 1,
                list("FOCUS L4" = FOCUS_2006_L4_mkin),
                quiet = TRUE)
-plot(mm.L4)
-
    
-
-
    plot of chunk unnamed-chunk-15
    
-
-
    The \(\chi^2\) error level of 3.3% as well as the plot suggest that the SFO model
-fits very well.  The error level at which the \(\chi^2\) test passes is slightly
-lower for the FOMC model. However, the difference appears negligible.
    
-
-
    summary(mm.L4[["SFO", 1]], data = FALSE)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:59 2018 
-## Date of summary: Thu Mar  1 14:24:59 2018 
+plot(mm.L4)
    
+
    
+
    The χ2 error level of 3.3% as well as the plot suggest that the SFO model fits very well. The error level at which the χ2 test passes is slightly lower for the FOMC model. However, the difference appears negligible.
    
+
    summary(mm.L4[["SFO", 1]], data = FALSE)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:25 2018 
+## Date of summary: Tue Jul 17 15:54:25 2018 
 ## 
 ## Equations:
 ## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 46 model solutions performed in 0.098 s
+## Fitted with method Port using 46 model solutions performed in 0.104 s
 ## 
 ## Weighting: none
 ## 
@@ -863,23 +744,19 @@ lower for the FOMC model. However, the difference appears negligible.
    
 ## 
 ## Estimated disappearance times:
 ##        DT50 DT90
-## parent  106  352
-
    
-
-
    summary(mm.L4[["FOMC", 1]], data = FALSE)
-
    
-
-
    ## mkin version:    0.9.46.3 
-## R version:       3.4.3 
-## Date of fit:     Thu Mar  1 14:24:59 2018 
-## Date of summary: Thu Mar  1 14:24:59 2018 
+## parent  106  352
    
+
    summary(mm.L4[["FOMC", 1]], data = FALSE)
    
+
    ## mkin version used for fitting:    0.9.47.1 
+## R version used for fitting:       3.5.1 
+## Date of fit:     Tue Jul 17 15:54:25 2018 
+## Date of summary: Tue Jul 17 15:54:25 2018 
 ## 
 ## 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 0.134 s
+## Fitted with method Port using 66 model solutions performed in 0.154 s
 ## 
 ## Weighting: none
 ## 
@@ -928,11 +805,37 @@ lower for the FOMC model. However, the difference appears negligible.
    
 ## 
 ## Estimated disappearance times:
 ##         DT50 DT90 DT50back
-## parent 108.9 1644    494.9
-
    
-
+## parent 108.9 1644    494.9
    
+
    
+
    
 
    References
    
+
    
+
    
+
    Ranke, Johannes. 2014. “Prüfung und Validierung von Modellierungssoftware als Alternative zu ModelMaker 4.0.” Umweltbundesamt Projektnummer 27452.
    
+
    
+
    
+
    
+
 
-
 
+
+
+
+
+
+
+
+
+
 
diff --git a/vignettes/FOCUS_Z.html b/vignettes/FOCUS_Z.html
index 95a67f94..ab32e936 100644
--- a/vignettes/FOCUS_Z.html
+++ b/vignettes/FOCUS_Z.html
@@ -11,13 +11,13 @@
 
 
 
-
+
 
 Example evaluation of FOCUS dataset Z
 
 
 
-
+
 
 
 
@@ -25,9 +25,9 @@
 
 
 
-
-
-
+
+
+
 
 
 
 
 
@@ -234,7 +236,7 @@ div.tocify {
 
 
    Example evaluation of FOCUS dataset Z
    
 
    Johannes Ranke
    
-
    2018-01-16
    
+
    2018-07-17
    
 
 
 
@@ -269,11 +271,11 @@ FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
    
 plot_sep(m.Z.2a)
    
 
    
 
    summary(m.Z.2a, data = FALSE)$bpar
    
-
    ##             Estimate se_notrans    t value     Pr(>t)   Lower     Upper
-## Z0_0      9.7015e+01   3.553135 2.7304e+01 1.6792e-21 91.4014 102.62838
-## k_Z0_sink 6.2135e-10   0.226894 2.7385e-09 5.0000e-01  0.0000       Inf
-## k_Z0_Z1   2.2360e+00   0.165073 1.3546e+01 7.3939e-14  1.8374   2.72107
-## k_Z1_sink 4.8212e-01   0.065854 7.3212e+00 3.5520e-08  0.4006   0.58024
    
+
    ##             Estimate se_notrans    t value     Pr(>t) Lower Upper
+## Z0_0      9.7015e+01   3.553140 2.7304e+01 1.6793e-21    NA    NA
+## k_Z0_sink 1.2790e-11   0.226895 5.6368e-11 5.0000e-01    NA    NA
+## k_Z0_Z1   2.2360e+00   0.165073 1.3546e+01 7.3938e-14    NA    NA
+## k_Z1_sink 4.8212e-01   0.065854 7.3212e+00 3.5520e-08    NA    NA
    
 
    As obvious from the parameter summary (the  component of the summary), the kinetic rate constant from parent compound Z to sink is very small and the t-test for this parameter suggests that it is not significantly different from zero. This suggests, in agreement with the analysis in the FOCUS kinetics report, to simplify the model by removing the pathway to sink.
    
 
    A similar result can be obtained when formation fractions are used in the model formulation:
    
 
    Z.2a.ff <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
@@ -285,10 +287,10 @@ plot_sep(m.Z.2a.ff)
    
 
    
 
    summary(m.Z.2a.ff, data = FALSE)$bpar
    
 
    ##            Estimate se_notrans t value     Pr(>t) Lower Upper
-## Z0_0       97.01488   3.553146 27.3039 1.6793e-21    NA    NA
-## k_Z0        2.23601   0.216847 10.3114 3.6617e-11    NA    NA
+## Z0_0       97.01488   3.553145 27.3039 1.6793e-21    NA    NA
+## k_Z0        2.23601   0.216849 10.3114 3.6623e-11    NA    NA
 ## k_Z1        0.48212   0.065854  7.3211 3.5520e-08    NA    NA
-## f_Z0_to_Z1  1.00000   0.101473  9.8548 9.7071e-11    NA    NA
    
+## f_Z0_to_Z1  1.00000   0.101473  9.8548 9.7068e-11    NA    NA
    
 
    Here, the ilr transformed formation fraction fitted in the model takes a very large value, and the backtransformed formation fraction from parent Z to Z1 is practically unity. Here, the covariance matrix used for the calculation of confidence intervals is not returned as the model is overparameterised.
    
 
    A simplified model is obtained by removing the pathway to the sink. 
    
 
    In the following, we use the parameterisation with formation fractions in order to be able to compare with the results in the FOCUS guidance, and as it makes it easier to use parameters obtained in a previous fit when adding a further metabolite.
    
@@ -300,8 +302,8 @@ plot_sep(m.Z.3)
    
 
    
 
    summary(m.Z.3, data = FALSE)$bpar
    
 
    ##      Estimate se_notrans t value     Pr(>t)    Lower   Upper
-## Z0_0 97.01488   2.681771  36.176 2.3636e-25 91.52152 102.508
-## k_Z0  2.23601   0.146862  15.225 2.2470e-15  1.95453   2.558
+## Z0_0 97.01488   2.681772  36.176 2.3636e-25 91.52152 102.508
+## k_Z0  2.23601   0.146861  15.225 2.2464e-15  1.95453   2.558
 ## k_Z1  0.48212   0.042687  11.294 3.0686e-12  0.40216   0.578
    
 
    As there is only one transformation product for Z0 and no pathway to sink, the formation fraction is internally fixed to unity.
    
 
@@ -314,7 +316,7 @@ plot_sep(m.Z.3)
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
 
    m.Z.5 <- mkinfit(Z.5, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.5)
    
-
    
+
    
 
    Finally, metabolite Z3 is added to the model. We use the optimised differential equation parameter values from the previous fit in order to accelerate the optimization.
    
 
    Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
@@ -325,22 +327,22 @@ plot_sep(m.Z.5)
    
 
    m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
                      parms.ini = m.Z.5$bparms.ode,
                      quiet = TRUE)
    
-
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation by method Port did not converge.
-## Convergence code is 1
    
+
    ## Warning in mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, parms.ini = m.Z.5$bparms.ode, : Optimisation by method Port did not converge:
+## false convergence (8)
    
 
    plot_sep(m.Z.FOCUS)
    
-
    
+
    
 
    summary(m.Z.FOCUS, data = FALSE)$bpar
    
-
    ##            Estimate se_notrans t value     Pr(>t)     Lower      Upper
-## Z0_0       96.84024   2.058814 47.0369 5.5723e-44 92.706852 100.973637
-## k_Z0        2.21540   0.118128 18.7543 7.7369e-25  1.990504   2.465708
-## k_Z1        0.47836   0.029294 16.3298 3.3443e-22  0.423035   0.540918
-## k_Z2        0.45166   0.044186 10.2218 3.0364e-14  0.371065   0.549767
-## k_Z3        0.05869   0.014290  4.1072 7.2560e-05  0.035983   0.095725
-## f_Z2_to_Z3  0.47147   0.057027  8.2676 2.7790e-11  0.360295   0.585556
    
+
    ##             Estimate se_notrans t value     Pr(>t)     Lower      Upper
+## Z0_0       96.837112   2.058861 47.0343 5.5877e-44 92.703779 100.970445
+## k_Z0        2.215368   0.118098 18.7587 7.6563e-25  1.990525   2.465609
+## k_Z1        0.478302   0.029289 16.3302 3.3408e-22  0.422977   0.540864
+## k_Z2        0.451617   0.044214 10.2144 3.1133e-14  0.371034   0.549702
+## k_Z3        0.058693   0.014296  4.1056 7.2924e-05  0.035994   0.095705
+## f_Z2_to_Z3  0.471516   0.057057  8.2639 2.8156e-11  0.360381   0.585548
    
 
    endpoints(m.Z.FOCUS)
    
 
    ## $ff
 ##   Z2_Z3 Z2_sink 
-## 0.47147 0.52853 
+## 0.47152 0.52848 
 ## 
 ## $SFORB
 ## logical(0)
@@ -348,9 +350,9 @@ plot_sep(m.Z.5)
    
 ## $distimes
 ##        DT50    DT90
 ## Z0  0.31288  1.0394
-## Z1  1.44901  4.8135
-## Z2  1.53466  5.0980
-## Z3 11.81037 39.2332
    
+## Z1  1.44918  4.8141
+## Z2  1.53481  5.0985
+## Z3 11.80973 39.2311
    
 
    This fit corresponds to the final result chosen in Appendix 7 of the FOCUS report. Confidence intervals returned by mkin are based on internally transformed parameters, however.
    
 
 
    
@@ -374,7 +376,7 @@ plot_sep(m.Z.mkin.1)
    
 
    ## Successfully compiled differential equation model from auto-generated C code.
    
 
    m.Z.mkin.3 <- mkinfit(Z.mkin.3, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.mkin.3)
    
-
    
+
    
 
    This results in a much better representation of the behaviour of the parent compound Z0.
    
 
    Finally, Z3 is added as well. These models appear overparameterised (no covariance matrix returned) if the sink for Z1 is left in the models.
    
 
    Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
@@ -386,7 +388,7 @@ plot_sep(m.Z.mkin.3)
    
                       parms.ini = m.Z.mkin.3$bparms.ode,
                       quiet = TRUE)
 plot_sep(m.Z.mkin.4)
    -

    +

    The error level of the fit, but especially of metabolite Z3, can be improved if the SFORB model is chosen for this metabolite, as this model is capable of representing the tailing of the metabolite decline phase.

    Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
                     Z1 = mkinsub("SFO", "Z2", sink = FALSE),
@@ -397,7 +399,7 @@ plot_sep(m.Z.mkin.4)
    parms.ini = m.Z.mkin.4$bparms.ode[1:4], quiet = TRUE) plot_sep(m.Z.mkin.5) -

    +

    The summary view of the backtransformed parameters shows that we get no confidence intervals due to overparameterisation. As the optimized is excessively small, it seems reasonable to fix it to zero.

    m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                        parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
@@ -409,7 +411,7 @@ plot_sep(m.Z.mkin.5a)

    As expected, the residual plots for Z0 and Z3 are more random than in the case of the all SFO model for which they were shown above. In conclusion, the model is proposed as the best-fit model for the dataset from Appendix 7 of the FOCUS report.

    A graphical representation of the confidence intervals can finally be obtained.

    mkinparplot(m.Z.mkin.5a)
    -

    +

    The endpoints obtained with this model are

    endpoints(m.Z.mkin.5a)
    ## $ff
@@ -418,11 +420,11 @@ plot_sep(m.Z.mkin.5a)
    ## ## $SFORB ## Z0_b1 Z0_b2 Z3_b1 Z3_b2 -## 2.4471373 0.0075126 0.0800076 0.0000000 +## 2.4471382 0.0075127 0.0800075 0.0000000 ## ## $distimes ## DT50 DT90 DT50_Z0_b1 DT50_Z0_b2 DT50_Z3_b1 DT50_Z3_b2 -## Z0 0.3043 1.1848 0.28325 92.265 NA NA +## Z0 0.3043 1.1848 0.28325 92.264 NA NA ## Z1 1.5148 5.0320 NA NA NA NA ## Z2 1.6414 5.4526 NA NA NA NA ## Z3 NA NA NA NA 8.6635 Inf diff --git a/vignettes/compiled_models.html b/vignettes/compiled_models.html index d8c5b19b..81bff548 100644 --- a/vignettes/compiled_models.html +++ b/vignettes/compiled_models.html @@ -12,7 +12,7 @@ - + Performance benefit by using compiled model definitions in mkin @@ -70,7 +70,7 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf

    Performance benefit by using compiled model definitions in mkin

    Johannes Ranke

    -

    2018-03-09

    +

    2018-07-17

    @@ -105,14 +105,14 @@ SFO_SFO <- mkinmod( } 
    ## Loading required package: rbenchmark
    ##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   1.980    1.000     1.979        0
-## 1 deSolve, not compiled            3  13.926    7.033    13.914        0
-## 2      Eigenvalue based            3   2.362    1.193     2.360        0
+## 3     deSolve, compiled            3   2.116    1.000     2.115        0
+## 1 deSolve, not compiled            3  16.563    7.828    16.555        0
+## 2      Eigenvalue based            3   2.599    1.228     2.597        0
 ##   user.child sys.child
 ## 3          0         0
 ## 1          0         0
 ## 2          0         0
    -

    We see that using the compiled model is by a factor of around 7 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.

    +

    We see that using the compiled model is by a factor of around 8 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.

    Model that can not be solved with Eigenvalues

    @@ -135,14 +135,14 @@ SFO_SFO <- mkinmod( }
    ## Successfully compiled differential equation model from auto-generated C code.
    ##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   3.437    1.000     3.433        0
-## 1 deSolve, not compiled            3  30.406    8.847    30.380        0
+## 2     deSolve, compiled            3   3.809    1.000     3.806        0
+## 1 deSolve, not compiled            3  35.885    9.421    35.866        0
 ##   user.child sys.child
 ## 2          0         0
 ## 1          0         0

    Here we get a performance benefit of a factor of 9 using the version of the differential equation model compiled from C code!

    -

    This vignette was built with mkin 0.9.46.3 on

    -
    ## R version 3.4.3 (2017-11-30)
+
    This vignette was built with mkin 0.9.47.1 on
    
+
    ## R version 3.5.1 (2018-07-02)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 9 (stretch)
    
 
    ## CPU model: AMD Ryzen 7 1700 Eight-Core Processor
    
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