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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-08, rtol = 1e-10, ...)
}
\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-8,
lower than in \code{\link{lsoda}}.
}
\item{rtol}{
Absolute error tolerance, passed to \code{\link{ode}}. Default is 1e-10,
much lower than 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_sink = 0.3), c(degradinol = 100), 0:20,
solution_type = "analytical")
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
solution_type = "eigen")
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 1:20,
solution_type = "analytical")[20,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
atol = 1e-20)[20,]
# The integration method does not make a lot of difference
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
atol = 1e-20, method = "ode45")[20,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
atol = 1e-20, method = "rk4")[20,]
# The number of output times used to make a lot of difference until the
# default for atol was adjusted
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
seq(0, 20, by = 0.1))[201,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
seq(0, 20, by = 0.01))[2001,]
}
\keyword{ manip }
|
