- Fitting and summaries now work with the new parameter transformations.

- The SFORB models with metabolites is broken (see TODO)
- Moved the vignette to the location recommended since R 2.14
- Added the missing documentation
- Commented out the schaefer_complex_case test, as this version of
  mkin is not able to fit a model without sink and therefore 
  mkin estimated parameters are quite different




git-svn-id: svn+ssh://svn.r-forge.r-project.org/svnroot/kinfit/pkg/mkin@22 edb9625f-4e0d-4859-8d74-9fd3b1da38cb

4 files changed, 117 insertions, 16 deletions

diff --git a/man/ilr.Rd b/man/ilr.Rd
index fef0d29..8bf7a72 100644
--- a/man/ilr.Rd
+++ b/man/ilr.Rd
@@ -17,22 +17,16 @@
     vectors with all elements being greater than zero.
   }
 }
-\details{
-}
 \value{
   The result of the forward or backward transformation. The returned components always 
   sum to 1 for the case of the inverse log-ratio transformation.
 }
 \references{
-%% ~put references to the literature/web site here ~
+  Peter Filzmoser, Karel Hron (2008) Outlier Detection for Compositional Data Using Robust Methods. Math Geosci 40 233-248
 }
 \author{
   René Lehmann and Johannes Ranke
 }
-\note{
-%%  ~~further notes~~
-}
-
 \seealso{
   Other implementations are in R packages \code{compositions} and \code{robCompositions}.
 }
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
new file mode 100644
index 0000000..af37f7c
--- /dev/null
+++ b/man/mkinpredict.Rd
@@ -0,0 +1,63 @@
+\name{mkinpredict}
+\alias{mkinpredict}
+\title{
+  Produce predictions from a kinetic model using specifc parameters
+}
+\description{
+  This function produces a time series for all the observed variables in a kinetic model
+  as specified by \code{\link{mkinmod}}, using a specific set of kinetic parameters and
+  initial values for the state variables.
+}
+\usage{
+mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve", map_output = TRUE, atol = 1e-06, ...)
+}
+\arguments{
+  \item{mkinmod}{
+  A kinetic model as produced by \code{\link{mkinmod}}.
+}
+  \item{odeparms}{
+  A numeric vector specifying the parameters used in the kinetic model, which is generally
+  defined as a set of ordinary differential equations.
+}
+  \item{odeini}{
+  A numeric vectory containing the initial values of the state variables of the model. Note
+  that the state variables can differ from the observed variables, for example in the case
+  of the SFORB model.
+}
+  \item{outtimes}{
+  A numeric vector specifying the time points for which model predictions should be 
+  generated.
+}
+  \item{solution_type}{
+  The method that should be used for producing the predictions. This should
+  generally be "analytical" if there is only one observed variable, and usually
+  "deSolve" in the case of several observed variables. The third possibility "eigen"
+  is faster but produces results that the author believes to be less accurate.
+}
+  \item{map_output}{
+  Boolean to specify if the output should list values for the observed variables (default)
+  or for all state variables (if set to FALSE). 
+}
+  \item{atol}{
+  Absolute error tolerance, passed to \code{\link{ode}}. Default is 1e-6 as in 
+  \code{\link{lsoda}}.
+}
+  \item{\dots}{
+  Further arguments passed to the ode solver in case such a solver is used.
+}
+}
+\value{
+  A matrix in the same format as the output of \code{\link{ode}}.
+}
+\author{
+  Johannes Ranke
+}
+\examples{
+  SFO <- mkinmod(degradinol = list(type = "SFO"))
+  mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 1:20, solution_type = "analytical")
+  mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 1:20, solution_type = "eigen")
+  mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 1:20, atol = 1e-20)
+  mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), 1:20, atol = 1e-20, method = "rk4")
+  mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100), (1:200)/10)
+}
+\keyword{ manip }
diff --git a/man/summary.mkinfit.Rd b/man/summary.mkinfit.Rd
index b3e7862..59b988a 100644
--- a/man/summary.mkinfit.Rd
+++ b/man/summary.mkinfit.Rd
@@ -11,8 +11,8 @@
   and residual values.

 }

 \usage{

-\method{summary}{mkinfit}(object, data = TRUE, distimes = TRUE, ff = TRUE, ...)

-\method{print}{summary.mkinfit}(x, digits = max(3, getOption("digits") - 3), tval = TRUE, ...)

+\method{summary}{mkinfit}(object, data = TRUE, distimes = TRUE, ...)

+\method{print}{summary.mkinfit}(x, digits = max(3, getOption("digits") - 3), ...)

 }

 

 \arguments{

@@ -28,16 +28,9 @@
   \item{distimes}{

   logical, indicating whether DT50 and DT90 values should be included.

 }

-  \item{ff}{

-  logical, indicating whether formation fractions should be included.

-}

   \item{digits}{

   Number of digits to use for printing

 }

-  \item{tval}{

-  Should the test statistic of the t-test for parameter significance be

-  printed? Defaults to \code{TRUE}. Saves vertical space if set to \code{FALSE}.

-}

   \item{\dots}{

   optional arguments passed to methods like \code{print}.

 }

diff --git a/man/transform_odeparms.Rd b/man/transform_odeparms.Rd
new file mode 100644
index 0000000..cc1c8f7
--- /dev/null
+++ b/man/transform_odeparms.Rd
@@ -0,0 +1,51 @@
+\name{transform_odeparms}
+\alias{transform_odeparms}
+\alias{backtransform_odeparms}
+\title{
+  Functions to transform and backtransform kinetic parameters for fitting
+}
+\description{
+  The transformations are intended to map parameters that should only take 
+  on restricted values to the full scale of real numbers. For kinetic rate
+  constants and other paramters that can only take on positive values, a
+  simple log transformation is used. For compositional parameters, such as
+  the formations fractions that should always sum up to 1 and can not be
+  negative, the \code{\link{ilr}} transformation is used.
+}
+\usage{
+transform_odeparms(parms, mod_vars)
+backtransform_odeparms(transparms, mod_vars)
+}
+\arguments{
+  \item{parms}{
+  Parameters of kinetic models as used in the differential equations.
+}
+  \item{transparms}{
+  Transformed parameters of kinetic models as used in the fitting procedure.
+}
+  \item{mod_vars}{
+  Names of the state variables in the kinetic model. These are used for 
+  grouping the formation fractions before \code{\link{ilr}} transformation.  
+}
+}
+\value{
+  A vector of transformed or backtransformed parameters with the same names
+  as the original parameters.
+}
+\author{
+  Johannes Ranke
+}
+\examples{
+SFO_SFO <- mkinmod(
+  parent = list(type = "SFO", to = "m1", sink = TRUE),
+  m1 = list(type = "SFO"))
+# Fit the model to the FOCUS example dataset D using defaults
+fit <- mkinfit(SFO_SFO, FOCUS_2006_D)
+summary(fit, data=FALSE) # See transformed and backtransformed parameters
+initials <- fit$start$initial
+transformed <- fit$start$transformed
+names(initials) <- names(transformed) <- rownames(fit$start)
+transform_odeparms(initials, c("parent", "m1"))
+backtransform_odeparms(transformed, c("parent", "m1"))
+}
+\keyword{ manip }