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-rw-r--r--man/D24_2014.Rd23
-rw-r--r--man/mkinds.Rd2
-rw-r--r--man/mkindsg.Rd5
-rw-r--r--man/saem.Rd13
4 files changed, 39 insertions, 4 deletions
diff --git a/man/D24_2014.Rd b/man/D24_2014.Rd
index d555d348..8a97dc47 100644
--- a/man/D24_2014.Rd
+++ b/man/D24_2014.Rd
@@ -25,6 +25,9 @@ context of pesticide registrations, as the use of the data may be
constrained by data protection regulations.
}
\details{
+The acronyms used for the 2,4-D transformation products are DCP for
+2,4-dichlorophenol and DCA for 2,4-dichloroanisole.
+
Data for the first dataset are from p. 685. Data for the other four
datasets were used in the preprocessed versions given in the kinetics
section (p. 761ff.), with the exception of residues smaller than 1 for DCP
@@ -46,6 +49,26 @@ m_D24_2 = mkinmod(D24 = mkinsub("DFOP", to = "DCP"),
DCP = mkinsub("SFO", to = "DCA"),
DCA = mkinsub("SFO"))
print(m_D24_2)
+D24_2014_data <- lapply(D24_2014$ds, function(x) x$data)
+names(D24_2014_data) <- sapply(D24_2014$ds, function(x) x$title)
+f_D24_2014_const <- mmkin(
+ models = list(
+ "SFO-SFO-SFO" = m_D24,
+ "DFOP-SFO-SFO" = m_D24_2),
+ data = D24_2014_data,
+ quiet = TRUE)
+print(f_D24_2014_const)
+plot(f_D24_2014_const[, 3])
+f_D24_2014_tc <- update(f_D24_2014_const, error_model = "tc")
+print(f_D24_2014_tc)
+plot(f_D24_2014_tc[, 3])
+# For dataset 3, the best fit is obtained using constant
+# variance and the DFOP-SFO-SFO model
+AIC(
+ f_D24_2014_const[["SFO-SFO-SFO", 3]],
+ f_D24_2014_const[["DFOP-SFO-SFO", 3]],
+ f_D24_2014_tc[["SFO-SFO-SFO", 3]],
+ f_D24_2014_tc[["DFOP-SFO-SFO", 3]])
}
}
\keyword{datasets}
diff --git a/man/mkinds.Rd b/man/mkinds.Rd
index a822bf80..a2c58300 100644
--- a/man/mkinds.Rd
+++ b/man/mkinds.Rd
@@ -17,7 +17,7 @@
\description{
At the moment this dataset class is hardly used in mkin. For example,
mkinfit does not take mkinds datasets as argument, but works with dataframes
-such as the on contained in the data field of mkinds objects. Some datasets
+such as the one contained in the data field of mkinds objects. Some datasets
provided by this package come as mkinds objects nevertheless.
}
\examples{
diff --git a/man/mkindsg.Rd b/man/mkindsg.Rd
index 3eee5562..3b6a9f61 100644
--- a/man/mkindsg.Rd
+++ b/man/mkindsg.Rd
@@ -23,6 +23,11 @@ so that combined evaluations are desirable.
Time normalisation factors are initialised with a value of 1 for each
dataset if no data are supplied.
}
+\note{
+Currently, no functions making use of the defined class structure
+are available in this package. Refer to \link{D24_2014} for an example
+dataset in this structure, with some example evaluations.
+}
\examples{
mdsg <- mkindsg$new("Experimental X", experimental_data_for_UBA_2019[6:10])
diff --git a/man/saem.Rd b/man/saem.Rd
index fd19fe59..5a125ab6 100644
--- a/man/saem.Rd
+++ b/man/saem.Rd
@@ -22,6 +22,7 @@ saem(object, ...)
omega.init = "auto",
covariates = NULL,
covariate_models = NULL,
+ center_covariates = c(NA, "median", "mean"),
no_random_effect = NULL,
error.init = c(1, 1),
nbiter.saemix = c(300, 100),
@@ -101,6 +102,10 @@ initialisation of \link[saemix:saemixModel]{saemix::saemixModel} is used for ome
variable, i.e. of the type 'parameter ~ covariate'. Covariates must be available
in the 'covariates' data frame.}
+\item{center_covariates}{Either NA, for no centering, or your
+preferred function for calculating the center, currently either
+median or mean.}
+
\item{no_random_effect}{Character vector of degradation parameters for
which there should be no variability over the groups. Only used
if the covariance model is not explicitly specified.}
@@ -199,9 +204,11 @@ print(f_saem_dfop_sfo)
plot(f_saem_dfop_sfo)
summary(f_saem_dfop_sfo, data = TRUE)
-# The following takes about 6 minutes
-f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",
- nbiter.saemix = c(200, 80))
+# The following took about 6 minutes and currently fails with
+# "Error in deSolve::lsoda(y = odeini, times = outtimes_deSolve, func = lsoda_func, :
+# illegal input detected before taking any integration steps - see written message"
+#f_saem_dfop_sfo_deSolve <- saem(f_mmkin["DFOP-SFO", ], solution_type = "deSolve",
+# nbiter.saemix = c(200, 80))
#anova(
# f_saem_dfop_sfo,

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