diff options
Diffstat (limited to 'R')
| -rw-r--r-- | R/mkinfit.R | 34 | ||||
| -rw-r--r-- | R/transform_odeparms.R | 41 |
2 files changed, 51 insertions, 24 deletions
diff --git a/R/mkinfit.R b/R/mkinfit.R index 326f4044..a623146e 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"))
diff --git a/R/transform_odeparms.R b/R/transform_odeparms.R index f56478f1..31200c76 100644 --- a/R/transform_odeparms.R +++ b/R/transform_odeparms.R @@ -1,6 +1,4 @@ -# $Id$
-
-# Copyright (C) 2010-2013 Johannes Ranke
+# Copyright (C) 2010-2014 Johannes Ranke
# Contact: jranke@uni-bremen.de
# This file is part of the R package mkin
@@ -18,17 +16,21 @@ # You should have received a copy of the GNU General Public License along with
# this program. If not, see <http://www.gnu.org/licenses/>
-transform_odeparms <- function(parms, mod_vars) {
+transform_odeparms <- function(parms, mod_vars,
+ transform_rates = TRUE,
+ transform_fractions = TRUE)
+{
# Set up container for transformed parameters
transparms <- parms
- # Log transformation for rate constants
+ # Log transformation for rate constants if requested
index_k <- grep("^k_", names(transparms))
if (length(index_k) > 0) {
- transparms[index_k] <- log(parms[index_k])
+ if(transform_rates) transparms[index_k] <- log(parms[index_k])
+ else transparms[index_k] <- parms[index_k]
}
- # Go through state variables and apply isotropic logratio transformation
+ # Go through state variables and apply isotropic logratio transformation if requested
for (box in mod_vars) {
indices_f <- grep(paste("^f", box, sep = "_"), names(parms))
f_names <- grep(paste("^f", box, sep = "_"), names(parms), value = TRUE)
@@ -37,32 +39,38 @@ transform_odeparms <- function(parms, mod_vars) { f <- parms[indices_f]
trans_f <- ilr(c(f, 1 - sum(f)))
names(trans_f) <- f_names
- transparms[indices_f] <- trans_f
+ if(transform_fractions) transparms[indices_f] <- trans_f
+ else transparms[indices_f] <- f
}
}
- # Transform parameters also for FOMC, DFOP and HS models
+ # Transform parameters also for FOMC, DFOP and HS models if requested
for (pname in c("alpha", "beta", "k1", "k2", "tb")) {
if (!is.na(parms[pname])) {
- transparms[pname] <- log(parms[pname])
+ transparms[pname] <- ifelse(transform_rates, log(parms[pname]), parms[pname])
+ transparms[pname] <- ifelse(transform_rates, log(parms[pname]), parms[pname])
}
}
if (!is.na(parms["g"])) {
g <- parms["g"]
- transparms["g"] <- ilr(c(g, 1- g))
+ transparms["g"] <- ifelse(transform_fractions, ilr(c(g, 1 - g)), g)
}
return(transparms)
}
-backtransform_odeparms <- function(transparms, mod_vars) {
+backtransform_odeparms <- function(transparms, mod_vars,
+ transform_rates = TRUE,
+ transform_fractions = TRUE)
+{
# Set up container for backtransformed parameters
parms <- transparms
# Exponential transformation for rate constants
index_k <- grep("^k_", names(parms))
if (length(index_k) > 0) {
- parms[index_k] <- exp(transparms[index_k])
+ if(transform_rates) parms[index_k] <- exp(transparms[index_k])
+ else parms[index_k] <- transparms[index_k]
}
# Go through state variables and apply inverse isotropic logratio transformation
@@ -73,19 +81,20 @@ backtransform_odeparms <- function(transparms, mod_vars) { if (n_paths > 0) {
f <- invilr(transparms[indices_f])[1:n_paths] # We do not need the last component
names(f) <- f_names
- parms[indices_f] <- f
+ if(transform_fractions) parms[indices_f] <- f
+ else parms[indices_f] <- transparms[indices_f]
}
}
# Transform parameters also for DFOP and HS models
for (pname in c("alpha", "beta", "k1", "k2", "tb")) {
if (!is.na(transparms[pname])) {
- parms[pname] <- exp(transparms[pname])
+ parms[pname] <- ifelse(transform_rates, exp(transparms[pname]), transparms[pname])
}
}
if (!is.na(transparms["g"])) {
g <- transparms["g"]
- parms["g"] <- invilr(g)[1]
+ parms["g"] <- ifelse(transform_fractions, invilr(g)[1], g)
}
return(parms)
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