From 98d684becd9495d370e1bcc8f9c7ca758caa4dd8 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 17 Nov 2016 22:58:28 +0100 Subject: Static documentation rebuilt by pkgdown::build_site() --- docs/articles/mkin.html | 28 ++++++++++++++++++---------- 1 file changed, 18 insertions(+), 10 deletions(-) (limited to 'docs/articles/mkin.html') 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.

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