diff options
Diffstat (limited to 'R/mkinfit.R')
| -rw-r--r-- | R/mkinfit.R | 34 |
1 files changed, 26 insertions, 8 deletions
diff --git a/R/mkinfit.R b/R/mkinfit.R index 326f404..a623146 100644 --- a/R/mkinfit.R +++ b/R/mkinfit.R @@ -30,6 +30,8 @@ mkinfit <- function(mkinmod, observed, method.ode = "lsoda",
method.modFit = "Marq",
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,
@@ -83,7 +85,9 @@ mkinfit <- function(mkinmod, observed, if(is.null(names(state.ini))) names(state.ini) <- mod_vars
# Transform initial parameter values for fitting
- transparms.ini <- transform_odeparms(parms.ini, mod_vars)
+ transparms.ini <- transform_odeparms(parms.ini, mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)
# Parameters to be optimised:
# Kinetic parameters in parms.ini whose names are not in fixed_parms
@@ -156,7 +160,9 @@ mkinfit <- function(mkinmod, observed, odeparms <- c(P[(length(state.ini.optim) + 1):length(P)], parms.fixed)
- parms <- backtransform_odeparms(odeparms, mod_vars)
+ parms <- backtransform_odeparms(odeparms, mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)
# Solve the system with current transformed parameter values
out <- mkinpredict(mkinmod, parms, odeini, outtimes,
@@ -241,6 +247,8 @@ mkinfit <- function(mkinmod, observed, # We need to return some more data for summary and plotting
fit$solution_type <- solution_type
+ fit$transform_rates <- transform_rates
+ fit$transform_fractions <- transform_fractions
# We also need the model for summary and plotting
fit$mkinmod <- mkinmod
@@ -252,19 +260,27 @@ mkinfit <- function(mkinmod, observed, # Collect initial parameter values in two dataframes
fit$start <- data.frame(value = c(state.ini.optim,
- backtransform_odeparms(parms.optim, mod_vars)))
+ backtransform_odeparms(parms.optim, mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)))
fit$start$type = c(rep("state", length(state.ini.optim)),
rep("deparm", length(parms.optim)))
fit$start$transformed = c(state.ini.optim, parms.optim)
fit$fixed <- data.frame(value = c(state.ini.fixed,
- backtransform_odeparms(parms.fixed, mod_vars)))
+ backtransform_odeparms(parms.fixed, mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)))
fit$fixed$type = c(rep("state", length(state.ini.fixed)),
rep("deparm", length(parms.fixed)))
- bparms.optim = backtransform_odeparms(fit$par, mod_vars)
+ bparms.optim = backtransform_odeparms(fit$par, mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)
bparms.fixed = backtransform_odeparms(c(state.ini.fixed, parms.fixed),
- mod_vars)
+ mod_vars,
+ transform_rates = transform_rates,
+ transform_fractions = transform_fractions)
bparms.all = c(bparms.optim, bparms.fixed)
# Collect observed, predicted, residuals and weighting
@@ -328,8 +344,10 @@ summary.mkinfit <- function(object, data = TRUE, distimes = TRUE, alpha = 0.05, par.lower <- par.upper <- object$par
par.lower[pname] <- param[pname, "Lower"]
par.upper[pname] <- param[pname, "Upper"]
- blci[pname] <- backtransform_odeparms(par.lower, mod_vars)[pname]
- buci[pname] <- backtransform_odeparms(par.upper, mod_vars)[pname]
+ blci[pname] <- backtransform_odeparms(par.lower, mod_vars,
+ object$transform_rates, object$transform_fractions)[pname]
+ buci[pname] <- backtransform_odeparms(par.upper, mod_vars,
+ object$transform_rates, object$transform_fractions)[pname]
}
bparam <- cbind(object$bparms.optim, blci, buci)
dimnames(bparam) <- list(pnames, c("Estimate", "Lower", "Upper"))
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