Example evaluation of FOCUS Example Dataset D • mkin

The following code defines the example dataset from Appendix 7 to the FOCUS kinetics report (FOCUS Work Group on Degradation Kinetics 2014, 354).
library(mkin, quietly = TRUE)
+library(mkin, quietly = TRUE)
 LOD = 0.5
-FOCUS_2006_Z = data.frame(
-  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
+FOCUS_2006_Z = data.frame(
+  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
         42, 61, 96, 124),
-  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
+  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
          2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
-  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
+  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
          1.6, 0.6, 0.5 * LOD, NA, NA, NA),
-  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
          0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
-  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
          25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
 
 FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
@@ -124,7 +125,7 @@
 m.Z.2a <- mkinfit(Z.2a, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.2a)
 
-summary(m.Z.2a, data = FALSE)$bpar
+summary(m.Z.2a, data = FALSE)$bpar
 ##             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
@@ -139,7 +140,7 @@
 m.Z.2a.ff <- mkinfit(Z.2a.ff, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.2a.ff)
 
-summary(m.Z.2a.ff, data = FALSE)$bpar
+summary(m.Z.2a.ff, data = FALSE)$bpar
 ##            Estimate se_notrans t value     Pr(>t) Lower Upper
 ## 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
@@ -154,7 +155,7 @@
 m.Z.3 <- mkinfit(Z.3, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.3)
 
-summary(m.Z.3, data = FALSE)$bpar
+summary(m.Z.3, data = FALSE)$bpar
 ##      Estimate se_notrans t value     Pr(>t)    Lower   Upper
 ## 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
@@ -186,7 +187,7 @@
 ## false convergence (8)
 plot_sep(m.Z.FOCUS)
 
-summary(m.Z.FOCUS, data = FALSE)$bpar
+summary(m.Z.FOCUS, data = FALSE)$bpar
 ##             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
@@ -223,7 +224,7 @@
 m.Z.mkin.1 <- mkinfit(Z.mkin.1, FOCUS_2006_Z_mkin, quiet = TRUE)
 plot_sep(m.Z.mkin.1)
 
-summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
+summary(m.Z.mkin.1, data = FALSE)$cov.unscaled
 ## NULL
 Therefore, a further stepwise model building is performed starting from the stage of parent and two metabolites, starting from the assumption that the model fit for the parent compound can be improved by using the SFORB model.
 Z.mkin.3 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
@@ -258,7 +259,7 @@
 
 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$bparms.ode[1:7],
+                       parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
                                      k_Z3_bound_free = 0),
                        fixed_parms = "k_Z3_bound_free",
                        quiet = TRUE)
@@ -320,9 +321,8 @@
 

 
 
-  Site built with pkgdown.
+  Site built with pkgdown 1.3.0.
 
-
       
 

 
diff --git a/docs/articles/web_only/compiled_models.html b/docs/articles/web_only/compiled_models.html
index 81d75821..a1fa69f5 100644
--- a/docs/articles/web_only/compiled_models.html
+++ b/docs/articles/web_only/compiled_models.html
@@ -1,18 +1,18 @@
 
-
+
 
 
 
 
 
 Performance benefit by using compiled model definitions in mkin • mkin
-
-
-
+
+
+
 
 
 
-
@@ -22,14 +22,15 @@
       
   
     
-      
       
         mkin
-        0.9.47.6
+        0.9.47.6
       
     
 
@@ -84,7 +85,7 @@
       Performance benefit by using compiled model definitions in mkin
                         Johannes Ranke
             
-            2018-11-26
+            2019-01-31
       
       
       compiled_models.Rmd
@@ -97,18 +98,18 @@
 
 Model that can also be solved with Eigenvalues
 This evaluation is taken from the example section of mkinfit. When using an mkin version equal to or greater than 0.9-36 and a C compiler (gcc) is available, you will see a message that the model is being compiled from autogenerated C code when defining a model using mkinmod. The mkinmod() function checks for presence of the gcc compiler using
-Sys.which("gcc")
+Sys.which("gcc")
 ##            gcc 
 ## "/usr/bin/gcc"
 First, we build a simple degradation model for a parent compound with one metabolite.
-library("mkin", quietly = TRUE)
+library("mkin", quietly = TRUE)
 SFO_SFO <- mkinmod(
   parent = mkinsub("SFO", "m1"),
   m1 = mkinsub("SFO"))
 ## Successfully compiled differential equation model from auto-generated C code.
 We can compare the performance of the Eigenvalue based solution against the compiled version and the R implementation of the differential equations using the benchmark package.
-if (require(rbenchmark)) {
-  b.1 <- benchmark(
+if (require(rbenchmark)) {
+  b.1 <- benchmark(
     "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                       solution_type = "deSolve",
                                       use_compiled = FALSE, quiet = TRUE),
@@ -117,17 +118,17 @@
     "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                   solution_type = "deSolve", quiet = TRUE),
     replications = 3)
-  print(b.1)
-  factor_SFO_SFO <- round(b.1["1", "relative"])
+  print(b.1)
+  factor_SFO_SFO <- round(b.1["1", "relative"])
 } else {
   factor_SFO_SFO <- NA
-  print("R package benchmark is not available")
+  print("R package benchmark is not available")
 }
 ## Lade nötiges Paket: rbenchmark
 ##                    test replications elapsed relative user.self sys.self
-## 3     deSolve, compiled            3   2.344    1.000     2.343    0.000
-## 1 deSolve, not compiled            3  18.171    7.752    18.152    0.008
-## 2      Eigenvalue based            3   2.887    1.232     2.885    0.000
+## 3     deSolve, compiled            3   2.319    1.000     2.317    0.000
+## 1 deSolve, not compiled            3  17.483    7.539    17.473    0.000
+## 2      Eigenvalue based            3   2.857    1.232     2.852    0.003
 ##   user.child sys.child
 ## 3          0         0
 ## 1          0         0
@@ -138,32 +139,32 @@
 
 Model that can not be solved with Eigenvalues
 This evaluation is also taken from the example section of mkinfit.
-if (require(rbenchmark)) {
+if (require(rbenchmark)) {
   FOMC_SFO <- mkinmod(
     parent = mkinsub("FOMC", "m1"),
     m1 = mkinsub( "SFO"))
 
-  b.2 <- benchmark(
+  b.2 <- benchmark(
     "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
                                       use_compiled = FALSE, quiet = TRUE),
     "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
     replications = 3)
-  print(b.2)
-  factor_FOMC_SFO <- round(b.2["1", "relative"])
+  print(b.2)
+  factor_FOMC_SFO <- round(b.2["1", "relative"])
 } else {
   factor_FOMC_SFO <- NA
-  print("R package benchmark is not available")
+  print("R package benchmark is not available")
 }
 ## Successfully compiled differential equation model from auto-generated C code.
 ##                    test replications elapsed relative user.self sys.self
-## 2     deSolve, compiled            3   4.173    1.000     4.169    0.000
-## 1 deSolve, not compiled            3  38.623    9.255    38.592    0.008
+## 2     deSolve, compiled            3   4.102    1.000     4.100        0
+## 1 deSolve, not compiled            3  37.059    9.034    37.041        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 0.9.47.6 on
-## R version 3.5.1 (2018-07-02)
+This vignette was built with mkin 0.9.47.5 on
+## R version 3.5.2 (2018-12-20)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
 ## Running under: Debian GNU/Linux 9 (stretch)
 ## CPU model: AMD Ryzen 7 1700 Eight-Core Processor
@@ -189,9 +190,8 @@
 

 
 
-  Site built with pkgdown.
+  Site built with pkgdown 1.3.0.
 
-
       
 

 
diff --git a/docs/authors.html b/docs/authors.html
index d80afb2e..dfea8ffd 100644
--- a/docs/authors.html
+++ b/docs/authors.html
@@ -1,6 +1,6 @@
 
 
-
+
   
   
 
@@ -9,17 +9,17 @@
 Authors • mkin
 
 
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+
 
 
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+
 
 
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+
 
 
-
+
 
 
 
@@ -35,7 +35,8 @@
 
 
 
-
+
+
 
 
+
 
 
 
 
 
 Kinetic Evaluation of Chemical Degradation Data • mkin
-
-
-
+
+
+
 
 
 
-
@@ -29,14 +29,15 @@
       
   
     
-      
       
         mkin
-        0.9.47.6
+        0.9.47.6
       
     
 
@@ -87,7 +88,7 @@
       
       

   
-    
+
 
 mkin
 
@@ -96,7 +97,7 @@
 
 Installation
 You can install the latest released version from CRAN from within R:
-install.packages("mkin")
+install.packages("mkin")
 
 
 
@@ -139,7 +140,7 @@
 
 
 News
-There is a ChangeLog, for the latest CRAN release and one for the github master branch.
+There is a ChangeLog, for the latest CRAN release and one for the github master branch.
 
 
 
@@ -161,7 +162,7 @@
 
   
 
-  
+  
     
 Links
 
@@ -180,7 +181,7 @@
 
 Developers
 
-Johannes Ranke 
 Author, maintainer, copyright holder   
+Johannes Ranke 
 Author, maintainer, copyright holder   
 All authors...
 
 
@@ -195,15 +196,13 @@
 
 
 
-
       
   Developed by Johannes Ranke.
 
 
 
-  Site built with pkgdown.
+  Site built with pkgdown 1.3.0.
 
-
       
 
 
diff --git a/docs/news/index.html b/docs/news/index.html
index 1b2455a8..1aa9e7a5 100644
--- a/docs/news/index.html
+++ b/docs/news/index.html
@@ -1,6 +1,6 @@
 
 
-
+
   
   
 
@@ -9,17 +9,17 @@
 Changelog • mkin
 
 
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+
 
 
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+
 
 
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+
 
 
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+
 
 
 
@@ -35,7 +35,8 @@
 
 
 
-
+
+
 
 
 
-
+
   
   
 
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 Calculated the AIC for a column of an mmkin object — AIC.mmkin • mkin
 
 
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+
 
 
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+
 
 
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+
 
 
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+
 
 
 
@@ -39,7 +39,8 @@
 
 
 
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+
 
 
+
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+  
+  
+
+
+
+Export a list of datasets in wide format to a CAKE study file — CAKE_export • mkin
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+
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+  
+
+  
+    
+      
+      
+  
+    
+      
+      
+        mkin
+        0.9.47.6
+      
+    
+
+    
+      
+        
+  Functions and data
+
+
+  
+    Articles
+     
+    
+  
+  
+    
+      Introduction to mkin
+    
+    
+      Example evaluation of FOCUS Example Dataset D
+    
+    
+      Example evaluation of FOCUS Laboratory Data L1 to L3
+    
+    
+      Example evaluation of FOCUS Example Dataset Z
+    
+    
+      Performance benefit by using compiled model definitions in mkin
+    
+    
+      Calculation of time weighted average concentrations with mkin
+    
+  
+
+
+  News
+
+      
+      
+      
+        
+      
+      
+    

+  

+

+
+      
+      
+
+
+  
+    
+    Export a list of datasets in wide format to a CAKE study file
+    
+    CAKE_export.Rd
+    
+
+    
+    
+    In addition to the datasets, the pathways in the degradation
+  model can be specified as well.
+    
+    
+
+    CAKE_export(ds, map = c(parent = "Parent"),
+  links = NA,
+  filename = "CAKE_export.csf", path = ".", overwrite = FALSE,
+  study = "Codlemone aerobic soil degradation",
+  description = "",
+  time_unit = "days",
+  res_unit = "% AR",
+  comment = "Created using mkin::CAKE_export",
+  date = Sys.Date(),
+  optimiser = "IRLS")
+    
+    Arguments
+    
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
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+    
+      
+      
+    
+    
+      
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+      
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+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    
+      
+      
+    
+    ds A named list of datasets in long format as compatible with
+    mkinfit.
map A character vector with CAKE compartment names (Parent, A1, ...),
+    named with the names used in the list of datasets.
links An optional character vector of target compartments, named with
+    the names of the source compartments. In order to make this
+    easier, the names are used as in the datasets supplied.
filename Where to write the result. Should end in .csf in order to be compatible
+    with CAKE.
path An optional path to the output file.
overwrite If TRUE, existing files are overwritten.
study The name of the study.
description An optional description.
time_unit The time unit for the residue data.
res_unit The unit used for the residues.
comment An optional comment.
date The date of file creation.
optimiser Can be OLS or IRLS.
+    
+    Value
+
+    The function is called for its side effect.
+    
+
+  
+  
+    Contents
+    
+      Arguments
+      
+      Value
+          
+
+    Author
+    Johannes Ranke
+  
+
+
+      
+      
+  Developed by Johannes Ranke.
+
+
+
+  Site built with pkgdown 1.3.0.
+
+      
+   
+
+  
+
+  
+
+
diff --git a/docs/reference/DFOP.solution.html b/docs/reference/DFOP.solution.html
index ad0ff22a..c82eb161 100644
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+++ b/docs/reference/DFOP.solution.html
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 Double First-Order in Parallel kinetics — DFOP.solution • mkin
 
 
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 Subsetting method for mmkin objects — [.mmkin • mkin
 
 
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 Results of fitting the DFOP model to Datasets A to B of FOCUS (2006) — FOCUS_2006_DFOP_ref_A_to_B • mkin
 
 
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 Results of fitting the FOMC model to Datasets A to F of FOCUS (2006) — FOCUS_2006_FOMC_ref_A_to_F • mkin
 
 
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 First-Order Multi-Compartment kinetics — FOMC.solution • mkin
 
 
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 Single First-Order Reversible Binding kinetics — SFORB.solution • mkin
 
 
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 Function to perform isometric log-ratio transformation — ilr • mkin
 
 
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 Function reference • mkin
 
 
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 Calculated the log-likelihood of a fitted mkinfit object — logLik.mkinfit • mkin
 
 
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 Datasets on aerobic soil metabolism of 2,4,5-T in six soils — mccall81_245T • mkin
 
 
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 A dataset class for mkin — mkinds • mkin
 
 
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 Calculate the minimum error to assume in order to pass the variance test — mkinerrmin • mkin
 
 
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 Fit a kinetic model to data with one or more state variables — mkinfit • mkin
 
 
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 Function to set up a kinetic model with one or more state variables — mkinmod • mkin
 
 
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 Function to plot the confidence intervals obtained using mkinfit — mkinparplot • mkin
 
 
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 Plot the observed data and the fitted model of an mkinfit object — mkinplot • mkin
 
 
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 Produce predictions from a kinetic model using specific parameters — mkinpredict • mkin
 
 
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 Function to plot residuals stored in an mkin object — mkinresplot • mkin
 
 
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 Function to set up a kinetic submodel for one state variable — mkinsub • mkin
 
 
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 Fit one or more kinetic models with one or more state variables to one or more datasets — mmkin • mkin
 
 
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 Plot the observed data and the fitted model of an mkinfit object — plot.mkinfit • mkin
 
 
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 Plot model fits (observed and fitted) and the residuals for a row or column of an mmkin object — plot.mmkin • mkin
 
 
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 Print mkinds objects — print.mkinds • mkin
 
 
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 Print mkinmod objects — print.mkinmod • mkin
 
 
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 Metabolism data set used for checking the software quality of KinGUI — schaefer07_complex_case • mkin
 
 
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 Two component error model — sigma_twocomp • mkin
 
 
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 Summary method for class "mkinfit" — summary.mkinfit • mkin
 
 
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 Synthetic datasets for one parent compound with two metabolites — synthetic_data_for_UBA_2014 • mkin
 
 
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 Three experimental datasets from two water sediment systems and one soil — test_data_from_UBA_2014 • mkin
 
 
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 Functions to transform and backtransform kinetic parameters for fitting — transform_odeparms • mkin
 
 
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Laboratory Data L3

Fit multiple models

Laboratory Data L4

Model that can not be solved with Eigenvalues

mkin

Installation

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News

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Links

Developers

Export a list of datasets in wide format to a CAKE study file

Arguments

Value

Contents

Author

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News
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There is a ChangeLog, for the latest CRAN release and one for the github master branch.
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There is a ChangeLog, for the latest CRAN release and one for the github master branch.

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