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-rw-r--r--R/transform_odeparms.R61
1 files changed, 39 insertions, 22 deletions
diff --git a/R/transform_odeparms.R b/R/transform_odeparms.R
index 0a25ee8c..f21d31fc 100644
--- a/R/transform_odeparms.R
+++ b/R/transform_odeparms.R
@@ -5,19 +5,19 @@
#' constants and other parameters that can only take on positive values, a
#' simple log transformation is used. For compositional parameters, such as the
#' formations fractions that should always sum up to 1 and can not be negative,
-#' the \code{\link{ilr}} transformation is used.
+#' the [ilr] transformation is used.
#'
#' The transformation of sets of formation fractions is fragile, as it supposes
#' the same ordering of the components in forward and backward transformation.
-#' This is no problem for the internal use in \code{\link{mkinfit}}.
+#' This is no problem for the internal use in [mkinfit].
#'
#' @param parms Parameters of kinetic models as used in the differential
#' equations.
#' @param transparms Transformed parameters of kinetic models as used in the
#' fitting procedure.
-#' @param mkinmod The kinetic model of class \code{\link{mkinmod}}, containing
+#' @param mkinmod The kinetic model of class [mkinmod], containing
#' the names of the model variables that are needed for grouping the
-#' formation fractions before \code{\link{ilr}} transformation, the parameter
+#' formation fractions before [ilr] transformation, the parameter
#' names and the information if the pathway to sink is included in the model.
#' @param transform_rates Boolean specifying if kinetic rate constants should
#' be transformed in the model specification used in the fitting for better
@@ -28,11 +28,15 @@
#' @param transform_fractions Boolean specifying if formation fractions
#' constants should be transformed in the model specification used in the
#' fitting for better compliance with the assumption of normal distribution
-#' of the estimator. The default (TRUE) is to do transformations. The g
-#' parameter of the DFOP and HS models are also transformed, as they can also
-#' be seen as compositional data. The transformation used for these
-#' transformations is the \code{\link{ilr}} transformation.
+#' of the estimator. The default (TRUE) is to do transformations.
+#' The g parameter of the DFOP model is also seen as a fraction.
+#' If a single fraction is transformed (g parameter of DFOP or only a single
+#' target variable e.g. a single metabolite plus a pathway to sink), a
+#' logistic transformation is used [stats::qlogis()]. In other cases, i.e. if
+#' two or more formation fractions need to be transformed whose sum cannot
+#' exceed one, the [ilr] transformation is used.
#' @return A vector of transformed or backtransformed parameters
+#' @importFrom stats plogis qlogis
#' @author Johannes Ranke
#' @examples
#'
@@ -91,8 +95,7 @@
#'
#' @export transform_odeparms
transform_odeparms <- function(parms, mkinmod,
- transform_rates = TRUE,
- transform_fractions = TRUE)
+ transform_rates = TRUE, transform_fractions = TRUE)
{
# We need the model specification for the names of the model
# variables and the information on the sink
@@ -119,8 +122,7 @@ transform_odeparms <- function(parms, mkinmod,
N <- parms[grep("^N", names(parms))]
transparms[names(N)] <- N
- # Go through state variables and apply isometric logratio transformation to
- # formation fractions if requested
+ # Go through state variables and transform formation fractions if requested
mod_vars = names(spec)
for (box in mod_vars) {
f <- parms[grep(paste("^f", box, sep = "_"), names(parms))]
@@ -128,9 +130,14 @@ transform_odeparms <- function(parms, mkinmod,
if (length(f) > 0) {
if(transform_fractions) {
if (spec[[box]]$sink) {
- trans_f <- ilr(c(f, 1 - sum(f)))
- trans_f_names <- paste("f", box, "ilr", 1:length(trans_f), sep = "_")
- transparms[trans_f_names] <- trans_f
+ if (length(f) == 1) {
+ trans_f_name <- paste("f", box, "qlogis", sep = "_")
+ transparms[trans_f_name] <- qlogis(f)
+ } else {
+ trans_f <- ilr(c(f, 1 - sum(f)))
+ trans_f_names <- paste("f", box, "ilr", 1:length(trans_f), sep = "_")
+ transparms[trans_f_names] <- trans_f
+ }
} else {
if (length(f) > 1) {
trans_f <- ilr(f)
@@ -161,7 +168,7 @@ transform_odeparms <- function(parms, mkinmod,
if (!is.na(parms["g"])) {
g <- parms["g"]
if (transform_fractions) {
- transparms["g_ilr"] <- ilr(c(g, 1 - g))
+ transparms["g_qlogis"] <- qlogis(g)
} else {
transparms["g"] <- g
}
@@ -207,20 +214,25 @@ backtransform_odeparms <- function(transparms, mkinmod,
N <- transparms[grep("^N", names(transparms))]
parms[names(N)] <- N
- # Go through state variables and apply inverse isometric logratio transformation
+ # Go through state variables and apply inverse transformations to formation fractions
mod_vars = names(spec)
for (box in mod_vars) {
# Get the names as used in the model
f_names = grep(paste("^f", box, sep = "_"), mkinmod$parms, value = TRUE)
+
# Get the formation fraction parameters
trans_f = transparms[grep(paste("^f", box, sep = "_"), names(transparms))]
if (length(trans_f) > 0) {
if(transform_fractions) {
- f <- invilr(trans_f)
- if (spec[[box]]$sink) {
- parms[f_names] <- f[1:length(f)-1]
+ if (any(grepl("qlogis", names(trans_f)))) {
+ parms[f_names] <- plogis(trans_f)
} else {
- parms[f_names] <- f
+ f <- invilr(trans_f)
+ if (spec[[box]]$sink) {
+ parms[f_names] <- f[1:length(f)-1]
+ } else {
+ parms[f_names] <- f
+ }
}
} else {
parms[names(trans_f)] <- trans_f
@@ -242,7 +254,12 @@ backtransform_odeparms <- function(transparms, mkinmod,
}
}
- # DFOP parameter g is treated as a fraction
+ # DFOP parameter g is now transformed using qlogis
+ if (!is.na(transparms["g_qlogis"])) {
+ g_qlogis <- transparms["g_qlogis"]
+ parms["g"] <- plogis(g_qlogis)
+ }
+ # In earlier times we used ilr for g, so we keep this around
if (!is.na(transparms["g_ilr"])) {
g_ilr <- transparms["g_ilr"]
parms["g"] <- invilr(g_ilr)[1]

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