From d8f31d1323998f33d07535f55c81be380d93ca45 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 9 Feb 2022 12:19:14 +0100 Subject: Adapt saemix interface to saemix 3.0 on CRAN --- vignettes/mkin.html | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) (limited to 'vignettes/mkin.html') diff --git a/vignettes/mkin.html b/vignettes/mkin.html index 58d49112..8a1a7641 100644 --- a/vignettes/mkin.html +++ b/vignettes/mkin.html @@ -1591,12 +1591,12 @@ div.tocify {

Introduction to mkin

Johannes Ranke

-

Last change 15 February 2021 (rebuilt 2021-09-16)

+

Last change 15 February 2021 (rebuilt 2022-02-08)

-

Wissenschaftlicher Berater, Kronacher Str. 12, 79639 Grenzach-Wyhlen, Germany
Privatdozent at the University of Bremen

+

Wissenschaftlicher Berater, Kronacher Str. 12, 79639 Grenzach-Wyhlen, Germany
Privatdozent at the University of Freiburg

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 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.

@@ -1713,7 +1713,7 @@ plot_sep(f_SFO_SFO_SFO, lpos = c("topright", "bottomright",

Schäfer, D., B. Mikolasch, P. Rainbird, and B. Harvey. 2007. “KinGUI: A New Kinetic Software Tool for Evaluations According to FOCUS Degradation Kinetics.” In Proceedings of the Xiii Symposium Pesticide Chemistry, edited by Del Re A. A. M., Capri E., Fragoulis G., and Trevisan M., 916–23. Piacenza.

-

Soetaert, Karline, and Thomas Petzoldt. 2010. “Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME.” Journal of Statistical Software 33 (3): 1–28. https://www.jstatsoft.org/v33/i03/.

+

Soetaert, Karline, and Thomas Petzoldt. 2010. “Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME.” Journal of Statistical Software 33 (3): 1–28. https://doi.org/10.18637/jss.v033.i03.

-- cgit v1.2.1