From 54cf070313c844f5ccf741fc7f1237fe2d260ded Mon Sep 17 00:00:00 2001 From: Johannes Ranke Date: Thu, 13 Oct 2016 17:40:36 +0200 Subject: Cleaning up a bit --- README.html | 81 +++++++++++++++++++++++++++++++++++++++++++++++++++++-------- 1 file changed, 71 insertions(+), 10 deletions(-) (limited to 'README.html') diff --git a/README.html b/README.html index 1e5ac529..b52ad556 100644 --- a/README.html +++ b/README.html @@ -10,18 +10,19 @@ + - + - - + + - + - + + + @@ -51,19 +80,48 @@ code { color: inherit; background-color: rgba(0, 0, 0, 0.04); } -img { - max-width:100%; - height: auto; +img { + max-width:100%; + height: auto; +} +.tabbed-pane { + padding-top: 12px; +} +button.code-folding-btn:focus { + outline: none; } + + +
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mkin

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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, or if several compartments are involved.

Installation

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  • As of version 0.9-39, fitting of several models to several datasets, optionally in parallel, is supported, see for example plot.mmkin.
  • 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).
  • If a C compiler is installed, the kinetic models are compiled from automatically generated C code, see
    - vignette compiled_models. The autogeneration of C code was inspired by the ccSolve package. Thanks to Karline Soetaert for her work on that.
    • +vignette compiled_models. The autogeneration of C code was inspired by the 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 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 RenĂ© Lehmann for the nice cooperation on this, especially the isometric 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.
  • The usual one-sided t-test for significant difference from zero is nevertheless shown based on estimators for the untransformed parameters.
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