From 7094934f1061563725f6caa8723dc3e23c8ca677 Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Wed, 16 Nov 2022 11:30:06 +0100 Subject: Update online docs --- docs/dev/articles/mkin.html | 81 ++++++++++++++----------- docs/dev/articles/web_only/saem_benchmarks.html | 24 ++++---- 2 files changed, 57 insertions(+), 48 deletions(-) (limited to 'docs/dev/articles') diff --git a/docs/dev/articles/mkin.html b/docs/dev/articles/mkin.html index 6bfb63bc..27e532af 100644 --- a/docs/dev/articles/mkin.html +++ b/docs/dev/articles/mkin.html @@ -34,7 +34,7 @@ mkin - 1.1.0 + 1.2.0 @@ -44,7 +44,7 @@ Functions and data
  • - Example evaluation of FOCUS Laboratory Data L1 to L3
  • - Example evaluation of FOCUS Example Dataset Z + Example evaluations of dimethenamid data from 2018 with nonlinear mixed-effects models +
    • +
  • + Short demo of the multistart method
  • Performance benefit by using compiled model definitions in mkin
    • +
  • + Example evaluation of FOCUS Example Dataset Z +
  • Calculation of time weighted average concentrations with mkin
    • @@ -72,7 +78,10 @@ Example evaluation of NAFTA SOP Attachment examples
  • - Some benchmark timings + Benchmark timings for mkin +
    • +
  • + Benchmark timings for saem.mmkin
    • @@ -103,7 +112,7 @@

    Introduction to mkin

    Johannes Ranke

    -

    Last change 15 February 2021 (rebuilt 2022-02-28)

    +

    Last change 15 February 2021 (rebuilt 2022-11-16)

    Source: vignettes/mkin.rmd @@ -118,34 +127,34 @@

    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.

    -library("mkin", quietly = TRUE)
-# Define the kinetic model
-m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"),
-                         M1 = mkinsub("SFO", "M2"),
-                         M2 = mkinsub("SFO"),
-                         use_of_ff = "max", quiet = TRUE)
-
-
-# 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,
-    f_M1_to_M2 = 0.9, k_M2 = log(2)/50),
-  c(parent = 100, M1 = 0, M2 = 0),
-  sampling_times)
-
-# 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"))
    +library("mkin", quietly = TRUE) +# Define the kinetic model +m_SFO_SFO_SFO <- mkinmod(parent = mkinsub("SFO", "M1"), + M1 = mkinsub("SFO", "M2"), + M2 = mkinsub("SFO"), + use_of_ff = "max", quiet = TRUE) + + +# 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, + f_M1_to_M2 = 0.9, k_M2 = log(2)/50), + c(parent = 100, M1 = 0, M2 = 0), + sampling_times) + +# 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"))

    @@ -224,10 +233,10 @@

    Ranke, J. 2021. ‘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.

    +

    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. https://jrwb.de/posters/Poster_SETAC_2012_Kinetic_parameter_uncertainty_model_parameterization_Lehmann_Ranke.pdf.

    -

    ———. 2015. “To T-Test or Not to T-Test, That Is the Question.” In XV Symposium on Pesticide Chemistry 2-4 September 2015. Piacenza. http://chem.uft.uni-bremen.de/ranke/posters/piacenza_2015.pdf.

    +

    ———. 2015. “To T-Test or Not to T-Test, That Is the Question.” In XV Symposium on Pesticide Chemistry 2-4 September 2015. Piacenza. https://jrwb.de/posters/piacenza_2015.pdf.

    Ranke, Johannes, and Stefan Meinecke. 2019. “Error Models for the Kinetic Evaluation of Chemical Degradation Data.” Environments 6 (12). https://doi.org/10.3390/environments6120124.

    @@ -262,7 +271,7 @@

    -

    Site built with pkgdown 2.0.2.

    +

    Site built with pkgdown 2.0.6.

    diff --git a/docs/dev/articles/web_only/saem_benchmarks.html b/docs/dev/articles/web_only/saem_benchmarks.html index e54bc38c..afff038f 100644 --- a/docs/dev/articles/web_only/saem_benchmarks.html +++ b/docs/dev/articles/web_only/saem_benchmarks.html @@ -112,7 +112,7 @@

    Benchmark timings for saem.mmkin

    Johannes Ranke

    -

    Last change 14 November 2022 (rebuilt 2022-11-15)

    +

    Last change 14 November 2022 (rebuilt 2022-11-16)

    Source: vignettes/web_only/saem_benchmarks.rmd @@ -309,10 +309,10 @@ Linux 1.2.0 3.2 -2.11 -4.632 -4.264 -4.93 +2.156 +4.647 +4.296 +4.951

    Two-component error fits for SFO, DFOP, SFORB and HS.

    @@ -332,10 +332,10 @@ Linux 1.2.0 3.2 -5.602 -7.373 -7.815 -7.831 +5.645 +7.415 +7.848 +7.967
    @@ -357,8 +357,8 @@ Linux 1.2.0 3.2 -24.014 -749.699 +24.182 +783.932 @@ -379,7 +379,7 @@ Linux 1.2.0 3.2 -1249.834 +1322.5 -- cgit v1.2.1