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@@ -36,73 +36,13 @@ detailed guidance and helpful tools have been developed as detailed in ## Usage -The simplest usage example that I can think of, using model shorthand notation -(available since mkin 0.9-32) and a built-in dataset is - - -```r -library(mkin) -fit <- mkinfit("SFO", FOCUS_2006_C, quiet = TRUE) -plot(fit, show_residuals = TRUE) -``` - - - - -```r -# Output not shown in this README to avoid distraction -summary(fit) -``` - -A still very simple usage example including the definition of the same data in R -code would be - - -```r -example_data = data.frame( - name = rep("parent", 9), - time = c(0, 1, 3, 7, 14, 28, 63, 91, 119), - value = c(85.1, 57.9, 29.9, 14.6, 9.7, 6.6, 4, 3.9, 0.6) -) -fit2 <- mkinfit("FOMC", example_data, quiet = TRUE) -plot(fit2, show_residuals = TRUE) -``` - - - -A fairly complex usage example using another built-in dataset: - - - - -```r -data <- mkin_wide_to_long(schaefer07_complex_case, time = "time") - -model <- mkinmod( - parent = mkinsub("SFO", c("A1", "B1", "C1"), sink = FALSE), - A1 = mkinsub("SFO", "A2"), - B1 = mkinsub("SFO"), - C1 = mkinsub("SFO"), - A2 = mkinsub("SFO"), use_of_ff = "max") - -fit3 <- mkinfit(model, data, method.modFit = "Port", quiet = TRUE) - -plot(fit3, show_residuals = TRUE) -``` - - - -```r -#summary(fit3) # Commented out to avoid distraction from README content -mkinparplot(fit3) -``` - - - -For more examples and to see results, have a look at the examples provided in the -[`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) +For a start, have a look a the code examples provided for +[`plot.mkinfit`](http://kinfit.r-forge.r-project.org/mkin_static/plot.mkinfit.html) +and +[`plot.mmkin`](http://kinfit.r-forge.r-project.org/mkin_static/plot.mmmkin.html), and +at the package vignettes +[`FOCUS L`](http://kinfit.r-forge.r-project.org/mkin_static/vignettes/FOCUS_L.html) and +[`FOCUS D`](http://kinfit.r-forge.r-project.org/mkin_static/vignettes/FOCUS_D.html). ## Features @@ -111,18 +51,18 @@ documentation or the package vignettes referenced from the 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. +* As of version 0.9-39, fitting of several models to several datasets, optionally in + parallel, is supported, see for example + [`plot.mmkin`](http://kinfit.r-forge.r-project.org/mkin_static/plot.mmkin.html) * 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. -* As of mkin 0.9-36, model solution for models with more than one observed - variable is based on the inline package. This is even faster than eigenvalue - based solution, at least in the example shown in the - [vignette `compiled_models`](http://rawgit.com/jranke/mkin/master/vignettes/compiled_models.html). +* If a C compiler is installed, the kinetic models are compiled from automatically + generated C code, see + [vignette `compiled_models`](http://kinfit.r-forge.r-project.org/mkin_static/vignettes/compiled_models.html). The autogeneration of C code was inspired by the [`ccSolve`](https://github.com/karlines/ccSolve) package. Thanks to Karline Soetaert for her work on that. @@ -151,14 +91,15 @@ documentation or the package vignettes referenced from the approximately reproduce the fit with other tools. * The chi-squared error level as defined in the FOCUS kinetics guidance (see below) is calculated for each observed variable. -* I recently added iteratively reweighted least squares in a similar way - it is done in KinGUII and CAKE (see below). Simply add the argument +* Iteratively reweighted least squares fitting is implemented in a similar way + as 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. * When a metabolite decline phase is not described well by SFO kinetics, - either IORE kinetics or SFORB kinetics can be used for the metabolite, - adding one respectively two parameters to the system. + either IORE kinetics (often producing failures of the integration algorithm) + or SFORB kinetics (working nicely) can be used for the metabolite, adding one + respectively two parameters to the system. ## GUI |