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+\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 }

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