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authorJohannes Ranke <jranke@uni-bremen.de>2018-09-18 15:15:55 +0200
committerJohannes Ranke <jranke@uni-bremen.de>2018-09-18 15:15:55 +0200
commit850aa313ba60c7b784d96cfdc8d4c22f2beb661a (patch)
tree1244a42d1e8a47a096a43d4c14634f3fe32e8778 /man
parenta2246bef55eb74f3ad608c28dc3b759af32a41b9 (diff)
Make mkinpredict generic and write a method for fits
Diffstat (limited to 'man')
-rw-r--r--man/mkinpredict.Rd42
1 files changed, 26 insertions, 16 deletions
diff --git a/man/mkinpredict.Rd b/man/mkinpredict.Rd
index 524abbb5..24b918dc 100644
--- a/man/mkinpredict.Rd
+++ b/man/mkinpredict.Rd
@@ -1,5 +1,7 @@
\name{mkinpredict}
\alias{mkinpredict}
+\alias{mkinpredict.mkinmod}
+\alias{mkinpredict.mkinfit}
\title{
Produce predictions from a kinetic model using specific parameters
}
@@ -9,13 +11,15 @@
kinetic parameters and initial values for the state variables.
}
\usage{
- mkinpredict(mkinmod, odeparms, odeini, outtimes, solution_type = "deSolve",
- use_compiled = "auto", method.ode = "lsoda", atol = 1e-08, rtol = 1e-10,
- map_output = TRUE, ...)
+ mkinpredict(x, odeparms, odeini, outtimes = seq(0, 120, by = 0.1),
+ solution_type = "deSolve", use_compiled = "auto", method.ode = "lsoda",
+ atol = 1e-08, rtol = 1e-10, map_output = TRUE, ...)
}
\arguments{
- \item{mkinmod}{
- A kinetic model as produced by \code{\link{mkinmod}}.
+ \item{x}{
+ A kinetic model as produced by \code{\link{mkinmod}}, or a kinetic
+ fit as fitted by \code{\link{mkinfit}}. In the latter case, the fitted
+ parameters are used for the prediction.
}
\item{odeparms}{
A numeric vector specifying the parameters used in the kinetic model, which
@@ -69,35 +73,35 @@
Johannes Ranke
}
\examples{
- SFO <- mkinmod(degradinol = list(type = "SFO"))
+ SFO <- mkinmod(degradinol = mkinsub("SFO"))
# Compare solution types
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = "analytical")
+ solution_type = "analytical")
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = "deSolve")
+ solution_type = "deSolve")
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = "deSolve", use_compiled = FALSE)
+ solution_type = "deSolve", use_compiled = FALSE)
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = "eigen")
+ solution_type = "eigen")
# Compare integration methods to analytical solution
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- solution_type = "analytical")[21,]
+ solution_type = "analytical")[21,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = "lsoda")[21,]
+ method = "lsoda")[21,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = "ode45")[21,]
+ method = "ode45")[21,]
mkinpredict(SFO, c(k_degradinol_sink = 0.3), c(degradinol = 100), 0:20,
- method = "rk4")[21,]
+ method = "rk4")[21,]
# rk4 is not as precise here
# 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,]
+ 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,]
+ seq(0, 20, by = 0.01))[2001,]
# Check compiled model versions - they are faster than the eigenvalue based solutions!
SFO_SFO = mkinmod(parent = list(type = "SFO", to = "m1"),
@@ -114,5 +118,11 @@
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),
solution_type = "deSolve", use_compiled = FALSE)[201,]))
+
+ \dontrun{
+ # Predict from a fitted model
+ f <- mkinfit(SFO_SFO, FOCUS_2006_C)
+ head(mkinpredict(f))
+ }
}
\keyword{ manip }

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