Remove trailing whitespace, clean headers

Also ignore test.R in the top level directory, as it is not meant to
be public

13 files changed, 85 insertions, 85 deletions

diff --git a/man/Extract.mmkin.Rd b/man/Extract.mmkin.Rd
index cd40e247..6e0c84e3 100644
--- a/man/Extract.mmkin.Rd
+++ b/man/Extract.mmkin.Rd
@@ -5,7 +5,7 @@
 \method{[}{mmkin}(x, i, j, ..., drop = FALSE)
 }
 \description{
- Subsetting method for mmkin objects. 
+ Subsetting method for mmkin objects.
 }
 \arguments{
 \item{x}{An \code{\link{mmkin} object}}
@@ -16,7 +16,7 @@
 
 \item{...}{Not used, only there to satisfy the generic method definition}
 
-\item{drop}{If FALSE, the method always returns an mmkin object, otherwise either 
+\item{drop}{If FALSE, the method always returns an mmkin object, otherwise either
   a list of mkinfit objects or a single mkinfit object.}
 }
 \value{
@@ -27,7 +27,7 @@
 }
 \examples{
   # Only use one core, to pass R CMD check --as-cran
-  fits <- mmkin(c("SFO", "FOMC"), list(B = FOCUS_2006_B, C = FOCUS_2006_C), 
+  fits <- mmkin(c("SFO", "FOMC"), list(B = FOCUS_2006_B, C = FOCUS_2006_C),
                 cores = 1, quiet = TRUE)
   fits["FOMC", ]
   fits[, "B"]
diff --git a/man/add_err.Rd b/man/add_err.Rd
index a0068b59..808edbc6 100644
--- a/man/add_err.Rd
+++ b/man/add_err.Rd
@@ -10,7 +10,7 @@
 }
 \usage{
   add_err(prediction, sdfunc,
-          n = 1000, LOD = 0.1, reps = 2, 
+          n = 1000, LOD = 0.1, reps = 2,
           digits = 1, seed = NA)
 }
 \arguments{
@@ -36,13 +36,13 @@
     The number of digits to which the values will be rounded.
   }
   \item{seed}{
-    The seed used for the generation of random numbers. If NA, the seed 
+    The seed used for the generation of random numbers. If NA, the seed
     is not set.
   }
 }
 \value{
   A list of datasets compatible with \code{\link{mmkin}}, i.e.
-  the components of the list are datasets compatible with 
+  the components of the list are datasets compatible with
   \code{\link{mkinfit}}.
 }
 \references{
@@ -80,7 +80,7 @@ names(d_SFO_SFO_err) <- paste("Dataset", 1:3)
 # Be quiet and use the faster Levenberg-Marquardt algorithm, as the datasets
 # are easy and examples are run often. Use only one core not to offend CRAN
 # checks
-f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO), 
+f_SFO_SFO <- mmkin(list("SFO-SFO" = m_SFO_SFO),
                    d_SFO_SFO_err, cores = 1,
                    quiet = TRUE, method.modFit = "Marq")
 
diff --git a/man/endpoints.Rd b/man/endpoints.Rd
index ad85622d..08773c3e 100644
--- a/man/endpoints.Rd
+++ b/man/endpoints.Rd
@@ -5,8 +5,8 @@ Function to calculate endpoints for further use from kinetic models fitted with
 }
 \description{
 This function calculates DT50 and DT90 values as well as formation fractions from kinetic models
-fitted with mkinfit. If the SFORB model was specified for one of the parents or metabolites, 
-the Eigenvalues are returned. These are equivalent to the rate constantes of the DFOP model, but 
+fitted with mkinfit. If the SFORB model was specified for one of the parents or metabolites,
+the Eigenvalues are returned. These are equivalent to the rate constantes of the DFOP model, but
 with the advantage that the SFORB model can also be used for metabolites.
 }
 \usage{
diff --git a/man/ilr.Rd b/man/ilr.Rd
index 9d1483f3..29bf7d87 100644
--- a/man/ilr.Rd
+++ b/man/ilr.Rd
@@ -18,7 +18,7 @@
   }
 }
 \value{
-  The result of the forward or backward transformation. The returned components always 
+  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{
diff --git a/man/mkin_long_to_wide.Rd b/man/mkin_long_to_wide.Rd
index 7f01b7f1..5dd335de 100644
--- a/man/mkin_long_to_wide.Rd
+++ b/man/mkin_long_to_wide.Rd
@@ -7,14 +7,14 @@
 mkin_long_to_wide(long_data, time = "time", outtime = "time")
 }
 \description{
-  This function takes a dataframe in the long form as required by \code{\link{modCost}} 
-  and converts it into a dataframe with one independent variable and several 
+  This function takes a dataframe in the long form as required by \code{\link{modCost}}
+  and converts it into a dataframe with one independent variable and several
   dependent variables as columns.
 }
 \arguments{
   \item{long_data}{
-  The dataframe must contain one variable called "time" with the time values specified by the 
-  \code{time} argument, one column called "name" with the grouping of the observed values, and 
+  The dataframe must contain one variable called "time" with the time values specified by the
+  \code{time} argument, one column called "name" with the grouping of the observed values, and
   finally one column of observed values called "value".
 }
   \item{time}{
diff --git a/man/mkin_wide_to_long.Rd b/man/mkin_wide_to_long.Rd
index cadfe4a2..b531c41c 100644
--- a/man/mkin_wide_to_long.Rd
+++ b/man/mkin_wide_to_long.Rd
@@ -7,12 +7,12 @@
 mkin_wide_to_long(wide_data, time = "t")
 }
 \description{
-  This function simply takes a dataframe with one independent variable and several 
+  This function simply takes a dataframe with one independent variable and several
   dependent variable and converts it into the long form as required by \code{\link{modCost}}.
 }
 \arguments{
   \item{wide_data}{
-  The dataframe must contain one variable with the time values specified by the 
+  The dataframe must contain one variable with the time values specified by the
   \code{time} argument and usually more than one column of observed values.
 }
   \item{time}{
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
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index f9eec532..524abbb5 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -43,8 +43,8 @@
     "lsoda" is performant, but sometimes fails to converge.
   }
   \item{use_compiled}{
-    If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}} 
-    model is used, even if is present. 
+    If set to \code{FALSE}, no compiled version of the \code{\link{mkinmod}}
+    model is used, even if is present.
   }
   \item{atol}{
     Absolute error tolerance, passed to \code{\link{ode}}. Default is 1e-8,
@@ -56,7 +56,7 @@
   }
   \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). 
+    variables (default) or for all state variables (if set to FALSE).
   }
   \item{\dots}{
     Further arguments passed to the ode solver in case such a solver is used.
@@ -71,20 +71,20 @@
 \examples{
   SFO <- mkinmod(degradinol = list(type = "SFO"))
   # Compare solution types
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, 
+  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, 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      solution_type = "deSolve")
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      solution_type = "deSolve", use_compiled = FALSE)
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      solution_type = "eigen")
 
 
   # Compare integration methods to analytical solution
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      solution_type = "analytical")[21,]
-  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20, 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      method = "lsoda")[21,]
   mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
 	      method = "ode45")[21,]
@@ -94,9 +94,9 @@
 
   # 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), 
+  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), 
+  mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100),
 	      seq(0, 20, by = 0.01))[2001,]
 
   # Check compiled model versions - they are faster than the eigenvalue based solutions!
@@ -108,11 +108,11 @@
                 solution_type = "eigen")[201,]))
   system.time(
     print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), 
+                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
                 solution_type = "deSolve")[201,]))
   system.time(
     print(mkinpredict(SFO_SFO, c(k_parent_m1 = 0.05, k_parent_sink = 0.1, k_m1_sink = 0.01),
-                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1), 
+                c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
                 solution_type = "deSolve", use_compiled = FALSE)[201,]))
 }
 \keyword{ manip }
diff --git a/man/mkinsub.Rd b/man/mkinsub.Rd
index 352c4097..84e38e21 100644
--- a/man/mkinsub.Rd
+++ b/man/mkinsub.Rd
@@ -4,7 +4,7 @@
   Function to set up a kinetic submodel for one state variable
 }
 \description{
-  This is a convenience function to set up the lists used as arguments for 
+  This is a convenience function to set up the lists used as arguments for
   \code{\link{mkinmod}}.
 }
 \usage{
@@ -12,15 +12,15 @@ mkinsub(submodel, to = NULL, sink = TRUE, full_name = NA)
 }
 \arguments{
   \item{submodel}{
-    Character vector of length one to specify the submodel type. See 
+    Character vector of length one to specify the submodel type. See
     \code{\link{mkinmod}} for the list of allowed submodel names.
   }
   \item{to}{
-    Vector of the names of the state variable to which a transformation 
+    Vector of the names of the state variable to which a transformation
     shall be included in the model.
   }
   \item{sink}{
-    Should a pathway to sink be included in the model in addition to the 
+    Should a pathway to sink be included in the model in addition to the
     pathways to other state variables?
   }
   \item{full_name}{
diff --git a/man/mmkin.Rd b/man/mmkin.Rd
index 689a1eb4..3a8d4a1f 100644
--- a/man/mmkin.Rd
+++ b/man/mmkin.Rd
@@ -26,11 +26,11 @@ mmkin(models, datasets,
     used when the \code{cluster} argument is \code{NULL}.
   }
   \item{cluster}{
-    A cluster as returned by \code{\link{makeCluster}} to be used for parallel 
+    A cluster as returned by \code{\link{makeCluster}} to be used for parallel
     execution.
   }
   \item{\dots}{
-    Further arguments that will be passed to \code{\link{mkinfit}}. 
+    Further arguments that will be passed to \code{\link{mkinfit}}.
   }
 }
 \value{
diff --git a/man/plot.mkinfit.Rd b/man/plot.mkinfit.Rd
index 89e5fb3c..a54bbbf6 100644
--- a/man/plot.mkinfit.Rd
+++ b/man/plot.mkinfit.Rd
@@ -6,33 +6,33 @@
 }
 \description{
   Solves the differential equations with the optimised and fixed parameters
-  from a previous successful call to \code{\link{mkinfit}} and plots 
+  from a previous successful call to \code{\link{mkinfit}} and plots
   the observed data together with the solution of the fitted model.
 }
 \usage{
 \method{plot}{mkinfit}(x, fit = x,
   obs_vars = names(fit$mkinmod$map),
-  xlab = "Time", ylab = "Observed", 
+  xlab = "Time", ylab = "Observed",
   xlim = range(fit$data$time),
   ylim = "default",
-  col_obs = 1:length(obs_vars), pch_obs = col_obs, 
+  col_obs = 1:length(obs_vars), pch_obs = col_obs,
   lty_obs = rep(1, length(obs_vars)),
   add = FALSE, legend = !add,
   show_residuals = FALSE, maxabs = "auto",
   sep_obs = FALSE, rel.height.middle = 0.9,
-  lpos = "topright", inset = c(0.05, 0.05), 
+  lpos = "topright", inset = c(0.05, 0.05),
   show_errmin = FALSE, errmin_digits = 3, \dots)
 plot_sep(fit, sep_obs = TRUE,  show_residuals = TRUE, show_errmin = TRUE, \dots)
 }
 \arguments{
   \item{x}{
-    Alias for fit introduced for compatibility with the generic S3 method.  
+    Alias for fit introduced for compatibility with the generic S3 method.
   }
   \item{fit}{
     An object of class \code{\link{mkinfit}}.
   }
   \item{obs_vars}{
-    A character vector of names of the observed variables for which the 
+    A character vector of names of the observed variables for which the
     data and the model should be plotted. Defauls to all observed variables
     in the model.
   }
@@ -66,7 +66,7 @@ plot_sep(fit, sep_obs = TRUE,  show_residuals = TRUE, show_errmin = TRUE, \dots)
   \item{show_residuals}{
     Should residuals be shown? If only one plot of the fits is shown, the
     residual plot is in the lower third of the plot? Otherwise, i.e. if
-    "sep_obs" is given, the residual plots will be located to the right of 
+    "sep_obs" is given, the residual plots will be located to the right of
     the plots of the fitted curves.
   }
   \item{maxabs}{
diff --git a/man/plot.mmkin.Rd b/man/plot.mmkin.Rd
index cfc7a35b..57f69c90 100644
--- a/man/plot.mmkin.Rd
+++ b/man/plot.mmkin.Rd
@@ -5,11 +5,11 @@
 }
 \description{
   When x is a row selected from an mmkin object (\code{\link{[.mmkin}}), the same model
-  fitted for at least one dataset is shown. When it is a column, the fit of at least one model 
+  fitted for at least one dataset is shown. When it is a column, the fit of at least one model
   to the same dataset is shown.
 }
 \usage{
-\method{plot}{mmkin}(x, main = "auto", legends = 1, errmin_var = "All data", errmin_digits = 3, 
+\method{plot}{mmkin}(x, main = "auto", legends = 1, errmin_var = "All data", errmin_digits = 3,
               cex = 0.7, rel.height.middle = 0.9, ...)
 }
 \arguments{
@@ -46,12 +46,12 @@
 }
 \examples{
   # Only use one core not to offend CRAN checks, use Levenberg-Marquardt for speed
-  fits <- mmkin(c("FOMC", "HS"), list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C), 
+  fits <- mmkin(c("FOMC", "HS"), list("FOCUS B" = FOCUS_2006_B, "FOCUS C" = FOCUS_2006_C),
                 cores = 1, quiet = TRUE, method.modFit = "Marq")
   plot(fits[, "FOCUS C"])
   plot(fits["FOMC", ])
 
-  # We can also plot a single fit, if we like the way mmkin works, but then the plot 
+  # We can also plot a single fit, if we like the way mmkin works, but then the plot
   # height should be smaller than the plot width (this is not possible for the html pages
   # generated by staticdocs, as far as I know).
   plot(fits["FOMC", "FOCUS C"]) # same as plot(fits[1, 2])
diff --git a/man/transform_odeparms.Rd b/man/transform_odeparms.Rd
index c6034424..71c179d7 100644
--- a/man/transform_odeparms.Rd
+++ b/man/transform_odeparms.Rd
@@ -5,7 +5,7 @@
   Functions to transform and backtransform kinetic parameters for fitting
 }
 \description{
-  The transformations are intended to map parameters that should only take 
+  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
@@ -17,9 +17,9 @@
   This is no problem for the internal use in \code{\link{mkinfit}}.
 }
 \usage{
-transform_odeparms(parms, mkinmod, 
+transform_odeparms(parms, mkinmod,
                    transform_rates = TRUE, transform_fractions = TRUE)
-backtransform_odeparms(transparms, mkinmod, 
+backtransform_odeparms(transparms, mkinmod,
                        transform_rates = TRUE, transform_fractions = TRUE)
 }
 \arguments{
@@ -32,22 +32,22 @@ backtransform_odeparms(transparms, mkinmod,
   \item{mkinmod}{
     The kinetic model of class \code{\link{mkinmod}}, containing the names of
     the model variables that are needed for grouping the formation fractions
-    before \code{\link{ilr}} transformation, the parameter names and 
-    the information if the pathway to sink is included in the model. 
+    before \code{\link{ilr}} transformation, the parameter names and
+    the information if the pathway to sink is included in the model.
   }
   \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.
   }
   \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 
-    to do transformations. The g parameter of the DFOP and HS models are also 
+    assumption of normal distribution of the estimator. The default (TRUE) is
+    to do transformations. 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 \code{\link{ilr}}
     transformation.
@@ -70,7 +70,7 @@ summary(fit, data=FALSE) # See transformed and backtransformed parameters
 
 \dontrun{
 fit.2 <- mkinfit(SFO_SFO, FOCUS_2006_D, transform_rates = FALSE)
-summary(fit.2, data=FALSE) 
+summary(fit.2, data=FALSE)
 }
 
 initials <- fit$start$value