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# mkin
[](https://cran.r-project.org/package=mkin)
[](https://travis-ci.com/jranke/mkin)
[](https://codecov.io/github/jranke/mkin)
The R package **mkin** provides calculation routines for the analysis of
chemical degradation data, including <b>m</b>ulticompartment <b>kin</b>etics as
needed for modelling the formation and decline of transformation products, or
if several compartments are involved.
## Installation
You can install the latest released version from
[CRAN](https://cran.r-project.org/package=mkin) from within R:
```r
install.packages("mkin")
```
## Background
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 and helpful tools have been developed as detailed in
'Credits and historical remarks' below.
## Usage
For a start, have a look a the code examples provided for
[`plot.mkinfit`](https://pkgdown.jrwb.de/mkin/reference/plot.mkinfit.html)
and
[`plot.mmkin`](https://pkgdown.jrwb.de/mkin/reference/plot.mmkin.html), and
at the package vignettes
[`FOCUS L`](https://pkgdown.jrwb.de/mkin/articles/FOCUS_L.html) and
[`FOCUS D`](https://pkgdown.jrwb.de/mkin/articles/FOCUS_D.html).
## Documentation
The HTML documentation is available at
[jrwb.de](https://pkgdown.jrwb.de/mkin), at
[github](http://jranke.github.io/mkin)
and at [R-Forge](http://kinfit.r-forge.r-project.org/mkin_static/index.html).
## Features
* Highly flexible model specification using
[`mkinmod`](https://pkgdown.jrwb.de/mkin/reference/mkinmod.html),
including equilibrium reactions and using the single first-order
reversible binding (SFORB) model, which will automatically create
two latent state variables for the observed variable.
* As of version 0.9-39, fitting of several models to several datasets, optionally in
parallel, is supported, see for example
[`plot.mmkin`](https://pkgdown.jrwb.de/mkin/reference/plot.mmkin.html).
* Model solution (forward modelling) in the function
[`mkinpredict`](https://pkgdown.jrwb.de/mkin/reference/mkinpredict.html)
is performed either using the analytical solution for the case of
parent only degradation, an eigenvalue based solution if only simple
first-order (SFO) or SFORB kinetics are used in the model, or
using a numeric solver from the `deSolve` package (default is `lsoda`).
* If a C compiler is installed, the kinetic models are compiled from automatically
generated C code, see
[vignette `compiled_models`](https://pkgdown.jrwb.de/mkin/articles/web_only/compiled_models.html).
The autogeneration of C code was
inspired by the [`ccSolve`](https://github.com/karlines/ccSolve) package. Thanks
to Karline Soetaert for her work on that.
* By default, kinetic rate constants and kinetic formation fractions are
transformed internally using
[`transform_odeparms`](https://pkgdown.jrwb.de/mkin/reference/transform_odeparms.html)
so their estimators can more reasonably be expected to follow
a normal distribution. This has the side effect that no constraints
are needed in the optimisation. Thanks to René Lehmann for the nice
cooperation on this, especially the isometric log-ratio transformation
that is now used for the formation fractions.
* A side effect of this is that when parameter estimates are backtransformed
to match the model definition, confidence intervals calculated from
standard errors are also backtransformed to the correct scale, and will
not include meaningless values like negative rate constants or
formation fractions adding up to more than 1, which can not occur in
a single experiment with a single defined radiolabel position.
* The usual one-sided t-test for significant difference from zero is nevertheless
shown based on estimators for the untransformed parameters.
* Summary and plotting functions. The `summary` of an `mkinfit` object is in
fact a full report that should give enough information to be able to
approximately reproduce the fit with other tools.
* The chi-squared error level as defined in the FOCUS kinetics guidance
(see below) is calculated for each observed variable.
* When a metabolite decline phase is not described well by SFO kinetics,
SFORB kinetics can be used for the metabolite.
* Three different error models can be selected using the argument `error_model`
to the [`mkinfit`](https://pkgdown.jrwb.de/mkin/reference/mkinfit.html)
function.
* The 'variance by variable' error model which is often fitted using
Iteratively Reweighted Least Squares (IRLS) should now be specified as
`error_model = "obs"`.
* A two-component error model similar to the one proposed by
[Rocke and Lorenzato](https://pkgdown.jrwb.de/mkin/reference/sigma_twocomp.html)
can be selected using the argument `error_model = "tc"`.
## GUI
There is a graphical user interface that I consider useful for real work. Please
refer to its [documentation page](http://kinfit.r-forge.r-project.org/gmkin_static)
for installation instructions and a manual.
## News
There is a ChangeLog, for the latest [CRAN release](https://cran.r-project.org/package=mkin/news/news.html)
and one for the [github master branch](https://github.com/jranke/mkin/blob/master/NEWS.md).
## Credits and historical remarks
`mkin` would not be possible without the underlying software stack consisting
of R and the package [deSolve](https://cran.r-project.org/package=deSolve).
In previous version, `mkin` was also using the functionality of the
[FME](https://cran.r-project.org/package=FME) package.
`mkin` could not have been written without me being introduced to regulatory fate
modelling of pesticides by Adrian Gurney during my time at Harlan Laboratories
Ltd (formerly RCC Ltd). `mkin` greatly profits from and largely follows
the work done by the
[FOCUS Degradation Kinetics Workgroup](http://esdac.jrc.ec.europa.eu/projects/degradation-kinetics),
as detailed in their guidance document from 2006, slightly updated in 2011 and
in 2014.
Also, it was inspired by the first version of KinGUI developed by
BayerCropScience, which is based on the MatLab runtime environment.
The companion package
[kinfit](http://kinfit.r-forge.r-project.org/kinfit_static/index.html) (now deprecated) was
[started in 2008](https://r-forge.r-project.org/scm/viewvc.php?view=rev&root=kinfit&revision=2) and
[first published](https://cran.r-project.org/src/contrib/Archive/kinfit/) on
CRAN on 01 May 2010.
The first `mkin` code was
[published on 11 May 2010](https://r-forge.r-project.org/scm/viewvc.php?view=rev&root=kinfit&revision=8) and the
[first CRAN version](https://cran.r-project.org/src/contrib/Archive/mkin)
on 18 May 2010.
In 2011, Bayer Crop Science started to distribute an R based successor to KinGUI named
KinGUII whose R code is based on `mkin`, but which added, amongst other
refinements, a closed source graphical user interface (GUI), iteratively
reweighted least squares (IRLS) optimisation of the variance for each of the
observed variables, and Markov Chain Monte Carlo (MCMC) simulation
functionality, similar to what is available e.g. in the `FME` package.
Somewhat in parallel, Syngenta has sponsored the development of an `mkin` and
KinGUII based GUI application called CAKE, which also adds IRLS and MCMC, is
more limited in the model formulation, but puts more weight on usability.
CAKE is available for download from the [CAKE
website](https://www.tessella.com/showcase/computer-assisted-kinetic-evaluation), where you can also
find a zip archive of the R scripts derived from `mkin`, published under the GPL
license.
Finally, there is
[KineticEval](http://github.com/zhenglei-gao/KineticEval), which contains
a further development of the scripts used for KinGUII, so the different tools
will hopefully be able to learn from each other in the future as well.
## References
<table>
<tr><td>Ranke J, Meinecke S (2019)
Error Models for the Kinetic Evaluation of Chemical Degradation Data
<i>Environments</i>
<b>6</b> (12) 124
<a href='https://doi.org/10.3390/environments6120124'>doi:10.3390/environments6120124</a>
</td></tr>
<tr><td>Ranke J, Wöltjen J, Meinecke S (2018)
Comparison of software tools for kinetic evaluation of chemical degradation data
<i>Environmental Sciences Europe</i>
<b>30</b> 17
<a href='https://doi.org/10.1186/s12302-018-0145-1'>doi:10.1186/s12302-018-0145-1</a>
</td></tr>
</table>
## Development
Contributions are welcome!
|
