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@@ -30,10 +30,51 @@ install_github("mkin", "jranke") ## 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 |