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mkinfit <- function(mkinmod, observed,
parms.ini = rep(0.1, length(mkinmod$parms)),
state.ini = c(100, rep(0, length(mkinmod$diffs) - 1)),
fixed_parms = rep(FALSE, length(mkinmod$parms)),
fixed_initials = c(FALSE, rep(TRUE, length(mkinmod$diffs) - 1)),
plot = NULL,
err = NULL, weight = "none", scaleVar = FALSE,
...)
{
# Name the parameters if they are not named yet
if(is.null(names(parms.ini))) names(parms.ini) <- mkinmod$parms
# Create a function calculating the differentials specified by the model
mkindiff <- function(t, state, parms) {
diffs <- vector()
for (box in names(mkinmod$diffs))
{
diffname <- paste("d", box, sep="_")
diffs[diffname] <- with(as.list(c(state, parms)),
eval(parse(text=mkinmod$diffs[[box]])))
}
return(list(c(diffs)))
}
# Name the inital parameter values if they are not named yet
if(is.null(names(state.ini))) names(state.ini) <- names(mkinmod$diffs)
# TODO: Collect parameters to be optimised
parms.optim <- parms.ini[!fixed_parms]
parms.fixed <- parms.ini[fixed_parms]
state.ini.optim <- state.ini[!fixed_initials]
state.ini.optim.boxnames <- names(state.ini.optim)
names(state.ini.optim) <- paste(names(state.ini.optim), "0", sep="_")
state.ini.fixed <- state.ini[fixed_initials]
# Define the model cost function
cost <- function(P)
{
if(length(state.ini.optim) > 0) {
odeini <- c(P[1:length(state.ini.optim)], state.ini.fixed)
names(odeini) <- c(state.ini.optim.boxnames, names(state.ini.fixed))
} else odeini <- state.ini.fixed
odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], parms.fixed)
# Solve the ODE
out <- ode(
y = odeini,
times = unique(observed$time),
func = mkindiff,
parms = odeparms)
# Output transformation for models with ghost compartments like SFORB
out_transformed <- data.frame(time = out[,"time"])
for (var in names(mkinmod$map)) {
if(length(mkinmod$map[[var]]) == 1) {
out_transformed[var] <- out[, var]
} else {
out_transformed[var] <- rowSums(out[, mkinmod$map[[var]]])
}
}
return(modCost(out_transformed, observed, y = "value",
err = err, weight = weight, scaleVar = scaleVar))
}
modFit(cost, c(state.ini.optim, parms.optim), ...)
}
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