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-rw-r--r--man/mkinpredict.Rd13
1 files changed, 5 insertions, 8 deletions
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index 1ba5b5f8..2c9192b7 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -85,13 +85,14 @@ is 1e-10, much lower than in \code{\link{lsoda}}.}
\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).}
+FALSE). Setting this to FALSE has no effect for analytical solutions,
+as these always return mapped output.}
\item{\dots}{Further arguments passed to the ode solver in case such a
solver is used.}
}
\value{
-A data frame with the solution in wide format
+A matrix with the numeric solution in wide format
}
\description{
This function produces a time series for all the observed variables in a
@@ -129,7 +130,7 @@ mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100),
mkinpredict(SFO, c(k_degradinol = 0.3), c(degradinol = 100),
seq(0, 20, by = 0.01))[2001,]
-# Check compiled model versions - they are faster than the eigenvalue based solutions!
+# Comparison of the performance of solution types
SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
m1 = list(type = "SFO"), use_of_ff = "max")
if(require(rbenchmark)) {
@@ -151,15 +152,11 @@ if(require(rbenchmark)) {
c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
solution_type = "analytical", use_compiled = FALSE)[201,])
}
- analytical = mkinpredict(SFO_SFO,
- c(k_parent = 0.15, f_parent_to_m1 = 0.5, k_m1 = 0.01),
- c(parent = 100, m1 = 0), seq(0, 20, by = 0.1),
- solution_type = "analytical", use_compiled = FALSE)[201,]
\dontrun{
# Predict from a fitted model
f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE)
- f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE, solution_type = "analytical")
+ f <- mkinfit(SFO_SFO, FOCUS_2006_C, quiet = TRUE, solution_type = "deSolve")
head(mkinpredict(f))
}

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