From 78ff1460c4e5b399bbab20f7b5b7f504dda8a6cd Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Tue, 12 Nov 2013 02:28:31 +0100 Subject: Some more work on the README --- README.md | 29 +++++++++++++++++------------ 1 file changed, 17 insertions(+), 12 deletions(-) diff --git a/README.md b/README.md index 16f5330..5e639e5 100644 --- a/README.md +++ b/README.md @@ -39,7 +39,7 @@ or the package vignettes referenced from the * 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 + 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 @@ -50,29 +50,33 @@ or the package vignettes referenced from the 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, +* Model optimisation with + [`mkinfit`](http://kinfit.r-forge.r-project.org/mkin_static/mkinfit.html) + 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 so their estimators can more reasonably be expected to follow + internally using + [`transform_odeparms`](http://kinfit.r-forge.r-project.org/mkin_static/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 + 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). + 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 will not occur in + 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 is in fact a full report - that should give enough information to be able to approximately - reproduce the fit with other tools. +* 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 + `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. + in a second stage after the primary optimisation algorithm has converged. ## Credits @@ -102,4 +106,5 @@ license. Finally, I just (2013-11-11) noticed the github repositories [StudyKin](http://github.com/zhenglei-gao/StudyKin) and [KineticEval](http://github.com/zhenglei-gao/KineticEval), the latter of which appears to be -actively developed. +actively developed, so the different tools will hopefully be able to learn +from each other in the future as well. -- cgit v1.2.1