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## Usage
For a start, have a look at the examples provided in the
-[mkinfit Documentation](http://kinfit.r-forge.r-project.org/mkin_static/mkinfit.html)
+[`mkinfit`](http://kinfit.r-forge.r-project.org/mkin_static/mkinfit.html)
+Documentation
or the package vignettes referenced from the
[mkin package documentation page](http://kinfit.r-forge.r-project.org/mkin_static/index.html)
+## Features
+
+* Highly flexible model specification using
+ [`mkinmod`](http://kinfit.r-forge.r-project.org/mkin_static/mkinmod.html),
+ including reverse 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`](http://kinfit.r-forge.r-project.org/mkin_static/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`).
+ These have decreasing efficiency, and are automatically chosen
+ by default.
+* Model optimisation 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 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 fracitons).
+* 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 will not occur in
+ a single experiment with a single defined radiolabel position).
+* Summary and plotting functions. The summary 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 optimisation step has converged.
+
+
## Credits
`mkin` would not be possible without the underlying software stack consisting

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