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100644 docs/articles/mkin_cache/html/unnamed-chunk-2_60bc93a2c97228ef4815e972498edefa.RData delete mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_60bc93a2c97228ef4815e972498edefa.rdb delete mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_60bc93a2c97228ef4815e972498edefa.rdx delete mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_f17bce9fa804585d9877abdce3dac24a.RData delete mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_f17bce9fa804585d9877abdce3dac24a.rdb delete mode 100644 docs/articles/mkin_cache/html/unnamed-chunk-2_f17bce9fa804585d9877abdce3dac24a.rdx (limited to 'docs/articles') diff --git a/docs/articles/FOCUS_D.R b/docs/articles/FOCUS_D.R index c3881e80..9eaf41f7 100644 --- a/docs/articles/FOCUS_D.R +++ b/docs/articles/FOCUS_D.R @@ -2,23 +2,3 @@ library(knitr) opts_chunk$set(tidy = FALSE, cache = TRUE) -## ----data---------------------------------------------------------------- -library("mkin") -print(FOCUS_2006_D) - -## ----model--------------------------------------------------------------- -SFO_SFO <- mkinmod(parent = mkinsub("SFO", "m1"), m1 = mkinsub("SFO")) -print(SFO_SFO$diffs) - -## ----fit----------------------------------------------------------------- -fit <- mkinfit(SFO_SFO, FOCUS_2006_D, quiet = TRUE) - -## ----plot, fig.height = 5------------------------------------------------ -plot(fit, show_residuals = TRUE) - -## ----plot_2, fig.height = 4---------------------------------------------- -mkinparplot(fit) - -## ------------------------------------------------------------------------ -summary(fit) - diff --git a/docs/articles/FOCUS_D.html b/docs/articles/FOCUS_D.html index 1c4edbd0..776e1093 100644 --- a/docs/articles/FOCUS_D.html +++ b/docs/articles/FOCUS_D.html @@ -41,7 +41,7 @@

Example evaluation of FOCUS Example Dataset D

Johannes Ranke

-

2016-11-04

+

2016-11-17

@@ -106,12 +106,12 @@ ## "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)
-

A plot of the fit including a residual plot for both observed variables is obtained using the plot method for mkinfit objects.

-
plot(fit, show_residuals = 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"))
+

Confidence intervals for the parameter estimates are obtained using the mkinparplot function.

mkinparplot(fit)
-

+

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

summary(fit)
## mkin version:    0.9.44.9000 
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@@ -1,8 +1,12 @@
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+colorout
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diff --git a/docs/articles/FOCUS_L.R b/docs/articles/FOCUS_L.R
index 858d483e..063e3d57 100644
--- a/docs/articles/FOCUS_L.R
+++ b/docs/articles/FOCUS_L.R
@@ -1,3 +1,50 @@
+## ---- include = FALSE----------------------------------------------------
+library(knitr)
+opts_chunk$set(tidy = FALSE, cache = FALSE)
+
+## ------------------------------------------------------------------------
+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)
+
+## ------------------------------------------------------------------------
+m.L1.SFO <- mkinfit("SFO", FOCUS_2006_L1_mkin, quiet = TRUE)
+summary(m.L1.SFO)
+
+## ----fig.width = 6, fig.height = 5---------------------------------------
+plot(m.L1.SFO, show_errmin = TRUE, main = "FOCUS L1 - SFO")
+
+## ----fig.width = 6, fig.height = 5---------------------------------------
+mkinresplot(m.L1.SFO, ylab = "Observed", xlab = "Time")
+
+## ----fig.width = 6, fig.height = 5---------------------------------------
+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)
+
+## ------------------------------------------------------------------------
+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)
+
+## ----fig.width = 7, fig.height = 6---------------------------------------
+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")
+
+## ----fig.width = 7, fig.height = 6---------------------------------------
+m.L2.FOMC <- mkinfit("FOMC", FOCUS_2006_L2_mkin, quiet = TRUE)
+plot(m.L2.FOMC, show_residuals = TRUE,
+     main = "FOCUS L2 - FOMC")
+summary(m.L2.FOMC, data = FALSE)
+
 ## ----fig.width = 7, fig.height = 6---------------------------------------
 m.L2.DFOP <- mkinfit("DFOP", FOCUS_2006_L2_mkin, quiet = TRUE)
 plot(m.L2.DFOP, show_residuals = TRUE, show_errmin = TRUE,
@@ -29,7 +76,7 @@ FOCUS_2006_L4_mkin <- mkin_wide_to_long(FOCUS_2006_L4)
 ## ----fig.height = 6------------------------------------------------------
 # 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), 
+               list("FOCUS L4" = FOCUS_2006_L4_mkin),
                quiet = TRUE)
 plot(mm.L4)
 
diff --git a/docs/articles/FOCUS_L.html b/docs/articles/FOCUS_L.html
index 4c3e5c9b..e7ec5308 100644
--- a/docs/articles/FOCUS_L.html
+++ b/docs/articles/FOCUS_L.html
@@ -41,7 +41,7 @@
       
Example evaluation of FOCUS Laboratory Data L1 to L3

                         
Johannes Ranke

             
-            
2016-11-04

+            
2016-11-17

           
 
     
@@ -53,7 +53,7 @@
 
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, 
+  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)

@@ -63,15 +63,15 @@ FOCUS_2006_L1_mkin <- summary(m.L1.SFO)
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:13:56 2016 
-## Date of summary: Fri Nov  4 17:13:56 2016 
+## Date of fit:     Thu Nov 17 22:58:18 2016 
+## Date of summary: Thu Nov 17 22:58:18 2016 
 ## 
 ## Equations:
-## d_parent = - k_parent_sink * parent
+## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 37 model solutions performed in 0.089 s
+## Fitted with method Port using 37 model solutions performed in 0.103 s
 ## 
 ## Weighting: none
 ## 
@@ -156,8 +156,8 @@ FOCUS_2006_L1_mkin <- 
summary(m.L1.FOMC, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:13:57 2016 
-## Date of summary: Fri Nov  4 17:13:57 2016 
+## Date of fit:     Thu Nov 17 22:58:19 2016 
+## Date of summary: Thu Nov 17 22:58:19 2016 
 ## 
 ## 
 ## Warning: Optimisation by method Port did not converge.
@@ -165,11 +165,11 @@ FOCUS_2006_L1_mkin <-  \(\chi^2\) 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 (Ranke, n.d.).

+
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 (Ranke 2014).

 
 

 
 Laboratory Data L2

@@ -236,7 +236,7 @@ FOCUS_2006_L2_mkin <-  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)
-plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE, 
+plot(m.L2.SFO, show_residuals = TRUE, show_errmin = TRUE,
      main = "FOCUS L2 - SFO")

 

 
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.

@@ -253,15 +253,15 @@ FOCUS_2006_L2_mkin <- 
summary(m.L2.FOMC, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:13:58 2016 
-## Date of summary: Fri Nov  4 17:13:58 2016 
+## Date of fit:     Thu Nov 17 22:58:20 2016 
+## Date of summary: Thu Nov 17 22:58:20 2016 
 ## 
 ## Equations:
-## d_parent = - (alpha/beta) * 1/((time/beta) + 1) * parent
+## 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 0.194 s
+## Fitted with method Port using 81 model solutions performed in 0.195 s
 ## 
 ## Weighting: none
 ## 
@@ -323,17 +323,17 @@ FOCUS_2006_L2_mkin <- 
summary(m.L2.DFOP, data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:13:59 2016 
-## Date of summary: Fri Nov  4 17:13:59 2016 
+## Date of fit:     Thu Nov 17 22:58:21 2016 
+## Date of summary: Thu Nov 17 22:58:21 2016 
 ## 
 ## Equations:
-## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-##            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 *
-##            time))) * parent
+## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
+##            exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
+##            exp(-k2 * time))) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 336 model solutions performed in 0.82 s
+## Fitted with method Port using 336 model solutions performed in 0.882 s
 ## 
 ## Weighting: none
 ## 
@@ -412,17 +412,17 @@ mm.L3 <- 
summary(mm.L3[["DFOP", 1]])

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:14:00 2016 
-## Date of summary: Fri Nov  4 17:14:00 2016 
+## Date of fit:     Thu Nov 17 22:58:22 2016 
+## Date of summary: Thu Nov 17 22:58:22 2016 
 ## 
 ## Equations:
-## d_parent = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) * exp(-k2 *
-##            time)) / (g * exp(-k1 * time) + (1 - g) * exp(-k2 *
-##            time))) * parent
+## d_parent/dt = - ((k1 * g * exp(-k1 * time) + k2 * (1 - g) *
+##            exp(-k2 * time)) / (g * exp(-k1 * time) + (1 - g) *
+##            exp(-k2 * time))) * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
-## Fitted with method Port using 137 model solutions performed in 0.336 s
+## Fitted with method Port using 137 model solutions performed in 0.338 s
 ## 
 ## Weighting: none
 ## 
@@ -504,7 +504,7 @@ FOCUS_2006_L4_mkin <- 
# 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), 
+               list("FOCUS L4" = FOCUS_2006_L4_mkin),
                quiet = TRUE)
 plot(mm.L4)

 

@@ -512,11 +512,11 @@ mm.L4 <- 
summary(mm.L4[["SFO", 1]], data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:14:01 2016 
-## Date of summary: Fri Nov  4 17:14:01 2016 
+## Date of fit:     Thu Nov 17 22:58:22 2016 
+## Date of summary: Thu Nov 17 22:58:23 2016 
 ## 
 ## Equations:
-## d_parent = - k_parent_sink * parent
+## d_parent/dt = - k_parent_sink * parent
 ## 
 ## Model predictions using solution type analytical 
 ## 
@@ -572,15 +572,15 @@ mm.L4 <- 
summary(mm.L4[["FOMC", 1]], data = FALSE)

 
## mkin version:    0.9.44.9000 
 ## R version:       3.3.2 
-## Date of fit:     Fri Nov  4 17:14:01 2016 
-## Date of summary: Fri Nov  4 17:14:01 2016 
+## Date of fit:     Thu Nov 17 22:58:23 2016 
+## Date of summary: Thu Nov 17 22:58:23 2016 
 ## 
 ## Equations:
-## d_parent = - (alpha/beta) * 1/((time/beta) + 1) * parent
+## 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 0.162 s
+## Fitted with method Port using 66 model solutions performed in 0.151 s
 ## 
 ## Weighting: none
 ## 
@@ -635,7 +635,7 @@ mm.L4 <-  References
 

 

-
Ranke, Johannes. n.d. “Prüfung und Validierung von Modellierungssoftware als Alternative zu ModelMaker 4.0.” Umweltbundesamt Projektnummer 27452.

+
Ranke, Johannes. 2014. “Prüfung und Validierung von Modellierungssoftware als Alternative zu ModelMaker 4.0.” Umweltbundesamt Projektnummer 27452.

 

 

 
diff --git a/docs/articles/FOCUS_Z.R b/docs/articles/FOCUS_Z.R
index 5fc8f123..5c70b57e 100644
--- a/docs/articles/FOCUS_Z.R
+++ b/docs/articles/FOCUS_Z.R
@@ -1,3 +1,25 @@
+## ----include=FALSE--------------------------------------------------
+require(knitr)
+opts_chunk$set(engine='R', tidy = FALSE, cache = TRUE)
+options(width=70)
+
+## ----FOCUS_2006_Z_data, echo=TRUE, eval=TRUE------------------------
+require(mkin)
+LOD = 0.5
+FOCUS_2006_Z = data.frame(
+  t = c(0, 0.04, 0.125, 0.29, 0.54, 1, 2, 3, 4, 7, 10, 14, 21,
+        42, 61, 96, 124),
+  Z0 = c(100, 81.7, 70.4, 51.1, 41.2, 6.6, 4.6, 3.9, 4.6, 4.3, 6.8,
+         2.9, 3.5, 5.3, 4.4, 1.2, 0.7),
+  Z1 = c(0, 18.3, 29.6, 46.3, 55.1, 65.7, 39.1, 36, 15.3, 5.6, 1.1,
+         1.6, 0.6, 0.5 * LOD, NA, NA, NA),
+  Z2 = c(0, NA, 0.5 * LOD, 2.6, 3.8, 15.3, 37.2, 31.7, 35.6, 14.5,
+         0.8, 2.1, 1.9, 0.5 * LOD, NA, NA, NA),
+  Z3 = c(0, NA, NA, NA, NA, 0.5 * LOD, 9.2, 13.1, 22.3, 28.4, 32.5,
+         25.2, 17.2, 4.8, 4.5, 2.8, 4.4))
+
+FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
+
 ## ----FOCUS_2006_Z_fits_1, echo=TRUE, fig.height=6-------------------
 Z.2a <- mkinmod(Z0 = mkinsub("SFO", "Z1"),
                 Z1 = mkinsub("SFO"))
@@ -32,9 +54,9 @@ plot_sep(m.Z.5)
 Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                    Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"), 
+                   Z3 = mkinsub("SFO"),
                    use_of_ff = "max")
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, 
+m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
                      parms.ini = m.Z.5$bparms.ode,
                      quiet = TRUE)
 plot_sep(m.Z.FOCUS)
@@ -62,7 +84,7 @@ Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
                     Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                     Z2 = mkinsub("SFO", "Z3"),
                     Z3 = mkinsub("SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, 
+m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
                       parms.ini = m.Z.mkin.3$bparms.ode,
                       quiet = TRUE)
 plot_sep(m.Z.mkin.4)
@@ -72,13 +94,13 @@ Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
                     Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                     Z2 = mkinsub("SFO", "Z3"),
                     Z3 = mkinsub("SFORB"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
+m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                       parms.ini = m.Z.mkin.4$bparms.ode[1:4],
                       quiet = TRUE)
 plot_sep(m.Z.mkin.5)
 
 ## ----FOCUS_2006_Z_fits_11a, echo=TRUE-------------------------------
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
+m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                        parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
                                      k_Z3_bound_free = 0),
                        fixed_parms = "k_Z3_bound_free",
diff --git a/docs/articles/FOCUS_Z.Rnw b/docs/articles/FOCUS_Z.Rnw
index 5a66db24..5abda0e1 100644
--- a/docs/articles/FOCUS_Z.Rnw
+++ b/docs/articles/FOCUS_Z.Rnw
@@ -3,7 +3,7 @@
 \documentclass[12pt,a4paper]{article}
 \usepackage{a4wide}
 \input{header}
-\hypersetup{  
+\hypersetup{
   pdftitle = {Example evaluation of FOCUS dataset Z},
   pdfsubject = {Manuscript},
   pdfauthor = {Johannes Ranke},
@@ -50,15 +50,15 @@ report \citep{FOCUSkinetics2011}, p.350.
 require(mkin)
 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, 
+  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)
@@ -66,9 +66,9 @@ FOCUS_2006_Z_mkin <- mkin_wide_to_long(FOCUS_2006_Z)
 
 \section{Parent compound and one metabolite}
 
-The next step is to set up the models used for the kinetic analysis. As the 
+The next step is to set up the models used for the kinetic analysis. As the
 simultaneous fit of parent and the first metabolite is usually straightforward,
-Step 1 (SFO for parent only) is skipped here. We start with the model 2a, 
+Step 1 (SFO for parent only) is skipped here. We start with the model 2a,
 with formation and decline of metabolite Z1 and the pathway from parent
 directly to sink included (default in mkin).
 
@@ -80,15 +80,15 @@ plot_sep(m.Z.2a)
 summary(m.Z.2a, data = FALSE)$bpar
 @
 
-As obvious from the parameter summary (the \texttt{bpar} component of the 
+As obvious from the parameter summary (the \texttt{bpar} component of the
 summary), the kinetic rate constant from parent compound Z to sink
-is negligible. Accordingly, the exact magnitude of the fitted parameter 
+is negligible. Accordingly, the exact magnitude of the fitted parameter
 \texttt{log k\_Z0\_sink} is ill-defined and the covariance matrix is not
-returned (not shown, would be visible in the complete summary). 
+returned (not shown, would be visible in the complete summary).
 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 
+A similar result can be obtained when formation fractions are used in the model
 formulation:
 
 <>=
@@ -104,16 +104,16 @@ summary(m.Z.2a.ff, data = FALSE)$bpar
 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. Again, the covariance matrix is not returned as the model is
-overparameterised. 
+overparameterised.
 
 The simplified model is obtained by setting the list component \texttt{sink} to
 \texttt{FALSE}.\footnote{If the model formulation without formation fractions
 is used, the same effect can be obtained by fixing the parameter \texttt{k\_Z\_sink}
-to a value of zero.} 
+to a value of zero.}
 
 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 
+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.
 
 <>=
@@ -130,10 +130,10 @@ to sink, the formation fraction is internally fixed to unity.
 \section{Including metabolites Z2 and Z3}
 
 As suggested in the FOCUS report, the pathway to sink was removed for metabolite Z1 as
-well in the next step. While this step appears questionable on the basis of the above results, it 
-is followed here for the purpose of comparison. Also, in the FOCUS report, it is 
+well in the next step. While this step appears questionable on the basis of the above results, it
+is followed here for the purpose of comparison. Also, in the FOCUS report, it is
 assumed that there is additional empirical evidence that Z1 quickly and exclusively
-hydrolyses to Z2. 
+hydrolyses to Z2.
 
 <>=
 Z.5 <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
@@ -151,9 +151,9 @@ accelerate the optimization.
 Z.FOCUS <- mkinmod(Z0 = mkinsub("SFO", "Z1", sink = FALSE),
                    Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                    Z2 = mkinsub("SFO", "Z3"),
-                   Z3 = mkinsub("SFO"), 
+                   Z3 = mkinsub("SFO"),
                    use_of_ff = "max")
-m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin, 
+m.Z.FOCUS <- mkinfit(Z.FOCUS, FOCUS_2006_Z_mkin,
                      parms.ini = m.Z.5$bparms.ode,
                      quiet = TRUE)
 plot_sep(m.Z.FOCUS)
@@ -167,13 +167,13 @@ transformed parameters, however.
 
 \section{Using the SFORB model for parent and metabolites}
 
-As the FOCUS report states, there is a certain tailing of the time course of metabolite 
-Z3. Also, the time course of the parent compound is not fitted very well using the 
+As the FOCUS report states, there is a certain tailing of the time course of metabolite
+Z3. Also, the time course of the parent compound is not fitted very well using the
 SFO model, as residues at a certain low level remain.
 
-Therefore, an additional model is offered here, using the single first-order 
+Therefore, an additional model is offered here, using the single first-order
 reversible binding (SFORB) model for metabolite Z3. As expected, the $\chi^2$
-error level is lower for metabolite Z3 using this model and the graphical 
+error level is lower for metabolite Z3 using this model and the graphical
 fit for Z3 is improved. However, the covariance matrix is not returned.
 
 <>=
@@ -198,7 +198,7 @@ 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 
+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
@@ -209,7 +209,7 @@ Z.mkin.4 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
                     Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                     Z2 = mkinsub("SFO", "Z3"),
                     Z3 = mkinsub("SFO"))
-m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin, 
+m.Z.mkin.4 <- mkinfit(Z.mkin.4, FOCUS_2006_Z_mkin,
                       parms.ini = m.Z.mkin.3$bparms.ode,
                       quiet = TRUE)
 plot_sep(m.Z.mkin.4)
@@ -224,7 +224,7 @@ Z.mkin.5 <- mkinmod(Z0 = mkinsub("SFORB", "Z1", sink = FALSE),
                     Z1 = mkinsub("SFO", "Z2", sink = FALSE),
                     Z2 = mkinsub("SFO", "Z3"),
                     Z3 = mkinsub("SFORB"))
-m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
+m.Z.mkin.5 <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                       parms.ini = m.Z.mkin.4$bparms.ode[1:4],
                       quiet = TRUE)
 plot_sep(m.Z.mkin.5)
@@ -233,10 +233,10 @@ 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
 \texttt{k\_Z3\_bound\_free} is excessively small, it seems reasonable to fix it to
-zero. 
+zero.
 
 <>=
-m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin, 
+m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
                        parms.ini = c(m.Z.mkin.5$bparms.ode[1:7],
                                      k_Z3_bound_free = 0),
                        fixed_parms = "k_Z3_bound_free",
@@ -244,7 +244,7 @@ m.Z.mkin.5a <- mkinfit(Z.mkin.5, FOCUS_2006_Z_mkin,
 plot_sep(m.Z.mkin.5a)
 @
 
-As expected, the residual plots for Z0 and Z3 are more random than in the case of the 
+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
 \texttt{Z.mkin.5a} is proposed as the best-fit model for the dataset from
 Appendix 7 of the FOCUS report.
@@ -261,8 +261,8 @@ The endpoints obtained with this model are
 endpoints(m.Z.mkin.5a)
 @
 
-It is clear the degradation rate of Z3 towards the end of the experiment 
-is very low as DT50\_Z3\_b2 (the second Eigenvalue of the system of two differential 
+It is clear the degradation rate of Z3 towards the end of the experiment
+is very low as DT50\_Z3\_b2 (the second Eigenvalue of the system of two differential
 equations representing the SFORB system for Z3, corresponding to the slower rate
 constant of the DFOP model) is reported to be infinity.  However, this appears
 to be a feature of the data.
diff --git a/docs/articles/FOCUS_Z.pdf b/docs/articles/FOCUS_Z.pdf
index 6f71d018..6f8929ea 100644
Binary files a/docs/articles/FOCUS_Z.pdf and b/docs/articles/FOCUS_Z.pdf differ
diff --git a/docs/articles/compiled_models.R b/docs/articles/compiled_models.R
index 5ce343cb..dd450e0d 100644
--- a/docs/articles/compiled_models.R
+++ b/docs/articles/compiled_models.R
@@ -15,12 +15,12 @@ SFO_SFO <- mkinmod(
 library("microbenchmark")
 library("ggplot2")
 mb.1 <- microbenchmark(
-  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 
-                                    solution_type = "deSolve", 
+  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
+                                    solution_type = "deSolve",
                                     use_compiled = FALSE, quiet = TRUE),
-  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D, 
+  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                solution_type = "eigen", quiet = TRUE),
-  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 
+  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                 solution_type = "deSolve", quiet = TRUE),
   times = 3, control = list(warmup = 0))
 
@@ -38,7 +38,7 @@ FOMC_SFO <- mkinmod(
   m1 = mkinsub( "SFO"))
 
 mb.2 <- microbenchmark(
-  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, 
+  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
                                     use_compiled = FALSE, quiet = TRUE),
   "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
   times = 3, control = list(warmup = 0))
diff --git a/docs/articles/compiled_models.html b/docs/articles/compiled_models.html
index 153841ae..1446a357 100644
--- a/docs/articles/compiled_models.html
+++ b/docs/articles/compiled_models.html
@@ -41,7 +41,7 @@
       
Performance benefit by using compiled model definitions in mkin

                         
Johannes Ranke

             
-            
2016-11-04

+            
2016-11-17

           
 
     
@@ -63,12 +63,12 @@ SFO_SFO <- 
library("microbenchmark")
 library("ggplot2")
 mb.1 <- microbenchmark(
-  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 
-                                    solution_type = "deSolve", 
+  "deSolve, not compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
+                                    solution_type = "deSolve",
                                     use_compiled = FALSE, quiet = TRUE),
-  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D, 
+  "Eigenvalue based" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                solution_type = "eigen", quiet = TRUE),
-  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D, 
+  "deSolve, compiled" = mkinfit(SFO_SFO, FOCUS_2006_D,
                                 solution_type = "deSolve", quiet = TRUE),
   times = 3, control = list(warmup = 0))

 
## Warning in microbenchmark(`deSolve, not compiled` = mkinfit(SFO_SFO,
@@ -78,21 +78,21 @@ mb.1 <- micr
 print(mb.1)

 
## Unit: milliseconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 6282.2220 6293.7637 6323.0479 6305.3053 6343.4608
-##       Eigenvalue based  873.2553  886.5949  903.6178  899.9345  918.7990
-##      deSolve, compiled  737.7899  738.8794  752.3343  739.9689  759.6065
+##  deSolve, not compiled 6251.2433 6291.2435 6315.5160 6331.2438 6347.6524
+##       Eigenvalue based  858.2035  903.1770  926.2132  948.1505  960.2181
+##      deSolve, compiled  721.0067  739.1361  745.9964  757.2656  758.4913
 ##        max neval cld
-##  6381.6162     3   c
-##   937.6634     3  b 
-##   779.2441     3 a

+##  6364.0611     3   c
+##   972.2856     3  b 
+##   759.7171     3 a

 
autoplot(mb.1)

 

-
We see that using the compiled model is by a factor of 8.5 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 8.4 faster than using the R version with the default ode solver, and it is even faster than the Eigenvalue based solution implemented in R which does not need iterative solution of the ODEs:

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

 
##                         median
-## deSolve, not compiled 8.521041
-## Eigenvalue based      1.216179
+## deSolve, not compiled 8.360665
+## Eigenvalue based      1.252071
 ## deSolve, compiled     1.000000

 
 

@@ -103,7 +103,7 @@ smb.1["median"]/smbm1 = mkinsub( "SFO"))

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

 
mb.2 <- microbenchmark(
-  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, 
+  "deSolve, not compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D,
                                     use_compiled = FALSE, quiet = TRUE),
   "deSolve, compiled" = mkinfit(FOMC_SFO, FOCUS_2006_D, quiet = TRUE),
   times = 3, control = list(warmup = 0))

@@ -114,18 +114,18 @@ smb.1["median"]/smbprint(mb.2)

 
## Unit: seconds
 ##                   expr       min        lq      mean    median        uq
-##  deSolve, not compiled 13.644880 13.648332 13.835874 13.651784 13.931372
-##      deSolve, compiled  1.422381  1.448574  1.495091  1.474767  1.531446
-##        max neval cld
-##  14.210959     3   b
-##   1.588125     3  a

+##  deSolve, not compiled 13.601046 13.602861 13.619563 13.604676 13.628821
+##      deSolve, compiled  1.341581  1.346263  1.348298  1.350944  1.351657
+##       max neval cld
+##  13.65297     3   b
+##   1.35237     3  a

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

 
##   median
 ## 1     NA
 ## 2     NA

 
autoplot(mb.2)

 

-
Here we get a performance benefit of a factor of 9.3 using the version of the differential equation model compiled from C code!

+
Here we get a performance benefit of a factor of 10.1 using the version of the differential equation model compiled from C code!

 
This vignette was built with mkin 0.9.44.9000 on

 
## R version 3.3.2 (2016-10-31)
 ## Platform: x86_64-pc-linux-gnu (64-bit)
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diff --git a/docs/articles/figure/FOCUS_2006_Z_fits_9-1.pdf b/docs/articles/figure/FOCUS_2006_Z_fits_9-1.pdf
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diff --git a/docs/articles/mkin.R b/docs/articles/mkin.R
index 175bd33b..67dc3623 100644
--- a/docs/articles/mkin.R
+++ b/docs/articles/mkin.R
@@ -1,22 +1,34 @@
+## ---- include = FALSE----------------------------------------------------
+require(knitr)
+opts_chunk$set(engine='R', tidy=FALSE)
+
 ## ---- echo = TRUE, cache = TRUE, fig = TRUE, fig.width = 8, fig.height = 7----
-require(mkin)
+library(mkin)
+# Define the kinetic model
 m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
                          M1 = mkinsub("SFO", "M2"),
-                         M2 = mkinsub("SFO"), 
+                         M2 = mkinsub("SFO"),
                          use_of_ff = "max", quiet = TRUE)
 
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 
+# Produce model predictions using some arbitrary parameters
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
-  c(k_parent = 0.03, 
-    f_parent_to_M1 = 0.5, k_M1 = log(2)/100, 
+  c(k_parent = 0.03,
+    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
     f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
   c(parent = 100, M1 = 0, M2 = 0),
   sampling_times)
 
-d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, function(x) 3, n = 1, seed = 123456789 )
+# Generate a dataset by adding normally distributed errors with
+# standard deviation 3, for two replicates at each sampling time
+d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
+                             sdfunc = function(x) 3,
+                             n = 1, seed = 123456789 )
 
+# Fit the model to the dataset
 f_SFO_SFO_SFO <- mkinfit(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[1]], quiet = TRUE)
 
+# Plot the results separately for parent and metabolites
 plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright", "bottomright"))
 
diff --git a/docs/articles/mkin.html b/docs/articles/mkin.html
index 8a24352c..4eed053a 100644
--- a/docs/articles/mkin.html
+++ b/docs/articles/mkin.html
@@ -41,7 +41,7 @@
       
mkin - Kinetic evaluation of chemical degradation data

                         
Johannes Ranke

             
-            
2016-11-04

+            
2016-11-17

           
 
     
@@ -51,25 +51,33 @@
 

 
 Abstract

 
In the regulatory evaluation of chemical substances like plant protection products (pesticides), biocides and other chemicals, degradation data play an important role. For the evaluation of pesticide degradation experiments, detailed guidance has been developed, based on nonlinear optimisation. The R add-on package mkin (Ranke 2016) implements fitting some of the models recommended in this guidance from within R and calculates some statistical measures for data series within one or more compartments, for parent and metabolites.

-
require(mkin)
+
library(mkin)
+# Define the kinetic model
 m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
                          M1 = mkinsub("SFO", "M2"),
-                         M2 = mkinsub("SFO"), 
+                         M2 = mkinsub("SFO"),
                          use_of_ff = "max", quiet = TRUE)
 
-sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 
+# Produce model predictions using some arbitrary parameters
+sampling_times = c(0, 1, 3, 7, 14, 28, 60, 90, 120)
 d_SFO_SFO_SFO <- mkinpredict(m_SFO_SFO_SFO,
-  c(k_parent = 0.03, 
-    f_parent_to_M1 = 0.5, k_M1 = log(2)/100, 
+  c(k_parent = 0.03,
+    f_parent_to_M1 = 0.5, k_M1 = log(2)/100,
     f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
   c(parent = 100, M1 = 0, M2 = 0),
   sampling_times)
 
-d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, function(x) 3, n = 1, seed = 123456789 )
+# Generate a dataset by adding normally distributed errors with
+# standard deviation 3, for two replicates at each sampling time
+d_SFO_SFO_SFO_err <- add_err(d_SFO_SFO_SFO, reps = 2,
+                             sdfunc = function(x) 3,
+                             n = 1, seed = 123456789 )
 
+# Fit the model to the dataset
 f_SFO_SFO_SFO <- mkinfit(m_SFO_SFO_SFO, d_SFO_SFO_SFO_err[[1]], quiet = TRUE)
 
+# Plot the results separately for parent and metabolites
 plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright", "bottomright"))

 

 

@@ -129,13 +137,13 @@ f_SFO_SFO_SFO <- http://focus.jrc.ec.europa.eu/dk.

 

 

-
R Development Core Team. 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. http://www.R-project.org.

+
R Development Core Team. 2016. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing. https://www.R-project.org.

 

 

-
Ranke, J. 2015. ‘Kinfit‘: Routines for Fitting Simple Kinetic Models to Chemical Degradation Data. http://CRAN.R-project.org/package=kinfit.

+
Ranke, J. 2015. ‘Kinfit‘: Routines for Fitting Simple Kinetic Models to Chemical Degradation Data. https://CRAN.R-project.org/package=kinfit.

 

 

-
———. 2016. ‘Mkin‘: Kinetic Evaluation of Chemical Degradation Data. http://CRAN.R-project.org/package=mkin.

+
———. 2016. ‘Mkin‘: Kinetic Evaluation of Chemical Degradation Data. https://CRAN.R-project.org/package=mkin.

 

 

 
Ranke, J., and R. Lehmann. 2012. “Parameter Reliability in Kinetic Evaluation of Environmental Metabolism Data - Assessment and the Influence of Model Specification.” In SETAC World 20-24 May. Berlin.

diff --git a/docs/articles/mkin_cache/html/__packages b/docs/articles/mkin_cache/html/__packages
index 03ece635..ff62e6df 100644
--- a/docs/articles/mkin_cache/html/__packages
+++ b/docs/articles/mkin_cache/html/__packages
@@ -1,13 +1,12 @@
 base
-datasets
-utils
-grDevices
-graphics
-stats
 knitr
 minpack.lm
 rootSolve
-methods
 inline
-parallel
 mkin
+colorout
+setwidth
+nvimcom
+rmarkdown
+microbenchmark
+ggplot2
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diff --git a/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png b/docs/articles/mkin_files/figure-html/unnamed-chunk-2-1.png
index 2e7e2244..d34e3805 100644
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diff --git a/docs/articles/references.bib b/docs/articles/references.bib
index da51602f..b465f828 100644
--- a/docs/articles/references.bib
+++ b/docs/articles/references.bib
@@ -47,7 +47,7 @@
   address = {Vienna, Austria},
   year = {2016},
   note = {{ISBN} 3-900051-07-0},
-  url = {http://www.R-project.org}
+  url = {https://www.R-project.org}
 }
 
 @MANUAL{pkg:kinfit,
@@ -55,14 +55,14 @@
 	degradation data},
   author = {J. Ranke},
   year = {2015},
-  url = {http://CRAN.R-project.org/package=kinfit}
+  url = {https://CRAN.R-project.org/package=kinfit}
 }
 
 @MANUAL{pkg:mkin,
   title = {`mkin`: {K}inetic evaluation of chemical degradation data},
   author = {J. Ranke},
   year = {2016},
-  url = {http://CRAN.R-project.org/package=mkin}
+  url = {https://CRAN.R-project.org/package=mkin}
 }
 
 @Inproceedings{   schaefer2007,
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