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-rw-r--r--man/mkinfit.Rd58
1 files changed, 29 insertions, 29 deletions
diff --git a/man/mkinfit.Rd b/man/mkinfit.Rd
index db2f7fda..f2df212f 100644
--- a/man/mkinfit.Rd
+++ b/man/mkinfit.Rd
@@ -5,11 +5,11 @@
}
\description{
This function uses the Flexible Modelling Environment package
- \code{\link{FME}} to create a function calculating the model cost, i.e. the
+ \code{\link{FME}} to create a function calculating the model cost, i.e. the
deviation between the kinetic model and the observed data. This model cost is
- then minimised using the Port algorithm \code{\link{nlminb}},
+ then minimised using the Port algorithm \code{\link{nlminb}},
using the specified initial or fixed parameters and starting values.
- Per default, parameters in the kinetic models are internally transformed in order
+ Per default, parameters in the kinetic models are internally transformed in order
to better satisfy the assumption of a normal distribution of their estimators.
In each step of the optimsation, the kinetic model is solved using the
function \code{\link{mkinpredict}}. The variance of the residuals for each
@@ -17,10 +17,10 @@
using the argument \code{reweight.method = "obs"}.
}
\usage{
-mkinfit(mkinmod, observed,
+mkinfit(mkinmod, observed,
parms.ini = "auto",
state.ini = "auto",
- fixed_parms = NULL, fixed_initials = names(mkinmod$diffs)[-1],
+ fixed_parms = NULL, fixed_initials = names(mkinmod$diffs)[-1],
from_max_mean = FALSE,
solution_type = c("auto", "analytical", "eigen", "deSolve"),
method.ode = "lsoda",
@@ -30,9 +30,9 @@ mkinfit(mkinmod, observed,
control.modFit = list(),
transform_rates = TRUE,
transform_fractions = TRUE,
- plot = FALSE, quiet = FALSE, err = NULL, weight = "none",
- scaleVar = FALSE,
- atol = 1e-8, rtol = 1e-10, n.outtimes = 100,
+ plot = FALSE, quiet = FALSE, err = NULL, weight = "none",
+ scaleVar = FALSE,
+ atol = 1e-8, rtol = 1e-10, n.outtimes = 100,
reweight.method = NULL,
reweight.tol = 1e-8, reweight.max.iter = 10,
trace_parms = FALSE, ...)
@@ -112,12 +112,12 @@ mkinfit(mkinmod, observed,
"lsoda" is performant, but sometimes fails to converge.
}
\item{use_compiled}{
- If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}}
+ If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}}
model is used, in the calls to \code{\link{mkinpredict}} even if
- a compiled verion is present.
+ a compiled verion is present.
}
\item{method.modFit}{
- The optimisation method passed to \code{\link{modFit}}.
+ The optimisation method passed to \code{\link{modFit}}.
In order to optimally deal with problems where local minima occur, the
"Port" algorithm is now used per default as it is less prone to get trapped
@@ -138,18 +138,18 @@ mkinfit(mkinmod, observed,
}
\item{maxit.modFit}{
Maximum number of iterations in the optimisation. If not "auto", this will
- be passed to the method called by \code{\link{modFit}}, overriding
+ be passed to the method called by \code{\link{modFit}}, overriding
what may be specified in the next argument \code{control.modFit}.
}
\item{control.modFit}{
Additional arguments passed to the optimisation method used by
- \code{\link{modFit}}.
+ \code{\link{modFit}}.
}
\item{transform_rates}{
Boolean specifying if kinetic rate constants should be transformed in the
model specification used in the fitting for better compliance with the
- assumption of normal distribution of the estimator. If TRUE, also
- alpha and beta parameters of the FOMC model are log-transformed, as well
+ assumption of normal distribution of the estimator. If TRUE, also
+ alpha and beta parameters of the FOMC model are log-transformed, as well
as k1 and k2 rate constants for the DFOP and HS models and the break point
tb of the HS model.
If FALSE, zero is used as a lower bound for the rates in the optimisation.
@@ -157,7 +157,7 @@ mkinfit(mkinmod, observed,
\item{transform_fractions}{
Boolean specifying if formation fractions constants should be transformed in the
model specification used in the fitting for better compliance with the
- assumption of normal distribution of the estimator. The default (TRUE) is
+ assumption of normal distribution of the estimator. The default (TRUE) is
to do transformations. If TRUE, the g parameter of the DFOP and HS
models are also transformed, as they can also be seen as compositional
data. The transformation used for these transformations is the
@@ -193,16 +193,16 @@ mkinfit(mkinmod, observed,
\item{n.outtimes}{
The length of the dataseries that is produced by the model prediction
function \code{\link{mkinpredict}}. This impacts the accuracy of
- the numerical solver if that is used (see \code{solution_type} argument.
+ the numerical solver if that is used (see \code{solution_type} argument.
The default value is 100.
}
\item{reweight.method}{
The method used for iteratively reweighting residuals, also known
as iteratively reweighted least squares (IRLS). Default is NULL,
the other method implemented is called "obs", meaning that each
- observed variable is assumed to have its own variance, this is
+ observed variable is assumed to have its own variance, this is
estimated from the fit and used for weighting the residuals
- in each iteration until convergence of this estimate up to
+ in each iteration until convergence of this estimate up to
\code{reweight.tol} or up to the maximum number of iterations
specified by \code{reweight.max.iter}.
}
@@ -217,19 +217,19 @@ mkinfit(mkinmod, observed,
Should a trace of the parameter values be listed?
}
\item{\dots}{
- Further arguments that will be passed to \code{\link{modFit}}.
+ Further arguments that will be passed to \code{\link{modFit}}.
}
}
\value{
- A list with "mkinfit" and "modFit" in the class attribute.
- A summary can be obtained by \code{\link{summary.mkinfit}}.
+ A list with "mkinfit" and "modFit" in the class attribute.
+ A summary can be obtained by \code{\link{summary.mkinfit}}.
}
\seealso{
Plotting methods \code{\link{plot.mkinfit}} and
- \code{\link{mkinparplot}}.
+ \code{\link{mkinparplot}}.
- Fitting of several models to several datasets in a single call to
- \code{\link{mmkin}}.
+ Fitting of several models to several datasets in a single call to
+ \code{\link{mmkin}}.
}
\note{
The implementation of iteratively reweighted least squares is inspired by the
@@ -238,7 +238,7 @@ mkinfit(mkinmod, observed,
other GUI derivative of mkin, sponsored by Syngenta.
}
\note{
- When using the "IORE" submodel for metabolites, fitting with
+ When using the "IORE" submodel for metabolites, fitting with
"transform_rates = TRUE" (the default) often leads to failures of the
numerical ODE solver. In this situation it may help to switch off the
internal rate transformation.
@@ -257,13 +257,13 @@ SFO_SFO <- mkinmod(
parent = mkinsub("SFO", "m1"),
m1 = mkinsub("SFO"))
# Fit the model to the FOCUS example dataset D using defaults
-print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
+print(system.time(fit <- mkinfit(SFO_SFO, FOCUS_2006_D,
solution_type = "eigen", quiet = TRUE)))
coef(fit)
endpoints(fit)
\dontrun{
# deSolve is slower when no C compiler (gcc) was available during model generation
-print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D,
+print(system.time(fit.deSolve <- mkinfit(SFO_SFO, FOCUS_2006_D,
solution_type = "deSolve")))
coef(fit.deSolve)
endpoints(fit.deSolve)
@@ -278,7 +278,7 @@ FOMC_SFO <- mkinmod(
fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D)
# Use starting parameters from parent only FOMC fit
fit.FOMC = mkinfit("FOMC", FOCUS_2006_D, plot=TRUE)
-fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D,
+fit.FOMC_SFO <- mkinfit(FOMC_SFO, FOCUS_2006_D,
parms.ini = fit.FOMC$bparms.ode, plot=TRUE)
# Use stepwise fitting, using optimised parameters from parent only fit, SFORB

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