mkin

The R package mkin provides calculation routines for the analysis of chemical degradation data, including multicompartment kinetics as needed for modelling the formation and decline of transformation products.

Installation

You can install the latest released version from CRAN from within R:

install.packages('mkin')

A development version is usually available from R-Forge:

install.packages('mkin', repos = 'http://r-forge.r-project.org')

If R-Forge is lacking behind or if you prefer, you can install directly from github using the devtools package:

require(devtools)
install_github("mkin", "jranke")

Usage

For a start, have a look at the examples provided in the mkinfit Documentation or the package vignettes referenced from the mkin package documentation page

Features

Highly flexible model specification using mkinmod, 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.
Model solution (forward modelling) in the function mkinpredict 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). These have decreasing efficiency, and are automatically chosen by default.
Model optimisation with mkinfit internally using the modFit function from the FME package, which uses the least-squares Levenberg-Marquardt algorithm from minpack.lm per default.
Kinetic rate constants and kinetic formation fractions are transformed internally using transform_odeparms 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 isotropic logration 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).
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.
I recently added iteratively reweighted least squares in a similar way it is done in KinGUII and CAKE (see below). Simply add the argument reweight = "obs" to your call to mkinfit and a separate variance componenent for each of the observed variables will be optimised in a second stage after the primary optimisation algorithm has converged.

Credits and historical remarks

mkin would not be possible without the underlying software stack consisting of R and the packages deSolve, minpack.lm and FME, to say the least.

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 was started in 2008 and first published on CRAN on 01 May 2010.

The first mkin code was published on 11 May 2010 and the first CRAN version on 18 May 2010.

After this, Bayer has developed 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, where you can also find a zip archive of the R scripts derived from mkin, published under the GPL license.

Finally, there is 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.

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