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-rw-r--r--R/parhist.R42
1 files changed, 29 insertions, 13 deletions
diff --git a/R/parhist.R b/R/parhist.R
index 10730873..5d498664 100644
--- a/R/parhist.R
+++ b/R/parhist.R
@@ -1,12 +1,15 @@
#' Plot parameter distributions from multistart objects
#'
-#' Produces a boxplot with all parameters from the multiple runs, divided by
-#' using their medians as in the paper by Duchesne et al. (2021).
+#' Produces a boxplot with all parameters from the multiple runs, scaled
+#' either by the parameters of the run with the highest likelihood,
+#' or by their medians as proposed in the paper by Duchesne et al. (2021).
#'
#' @param object The [multistart] object
-#' @param \dots Passed to [boxplot]
+#' @param scale By default, scale parameters using the best available fit.
+#' If 'median', parameters are scaled using the median parameters from all fits.
#' @param main Title of the plot
#' @param lpos Positioning of the legend.
+#' @param \dots Passed to [boxplot]
#' @references Duchesne R, Guillemin A, Gandrillon O, Crauste F. Practical
#' identifiability in the frame of nonlinear mixed effects models: the example
#' of the in vitro erythropoiesis. BMC Bioinformatics. 2021 Oct 4;22(1):478.
@@ -14,7 +17,9 @@
#' @seealso [multistart]
#' @importFrom stats median
#' @export
-parhist <- function(object, lpos = "bottomleft", main = "", ...) {
+parhist <- function(object, scale = c("best", "median"),
+ lpos = "bottomleft", main = "", ...)
+{
oldpar <- par(no.readonly = TRUE)
on.exit(par(oldpar, no.readonly = TRUE))
@@ -48,23 +53,34 @@ parhist <- function(object, lpos = "bottomleft", main = "", ...) {
colnames(all_parms)[1:length(degparm_names)] <- degparm_names
}
- median_parms <- apply(all_parms, 2, median)
- start_scaled_parms <- rep(NA_real_, length(orig_parms))
- names(start_scaled_parms) <- names(orig_parms)
+ scale <- match.arg(scale)
+ parm_scale <- switch(scale,
+ best = all_parms[which.best(object), ],
+ median = apply(all_parms, 2, median)
+ )
- orig_scaled_parms <- orig_parms / median_parms
- all_scaled_parms <- t(apply(all_parms, 1, function(x) x / median_parms))
- start_scaled_parms[names(start_parms)] <-
- start_parms / median_parms[names(start_parms)]
+ # Boxplots of all scaled parameters
+ all_scaled_parms <- t(apply(all_parms, 1, function(x) x / parm_scale))
boxplot(all_scaled_parms, log = "y", main = main, ,
ylab = "Normalised parameters", ...)
- points(orig_scaled_parms, col = 2, cex = 2)
+ # Show starting parameters
+ start_scaled_parms <- rep(NA_real_, length(orig_parms))
+ names(start_scaled_parms) <- names(orig_parms)
+ start_scaled_parms[names(start_parms)] <-
+ start_parms / parm_scale[names(start_parms)]
points(start_scaled_parms, col = 3, cex = 3)
+
+ # Show parameters of original run
+ orig_scaled_parms <- orig_parms / parm_scale
+ points(orig_scaled_parms, col = 2, cex = 2)
+
+ abline(h = 1, lty = 2)
+
legend(lpos, inset = c(0.05, 0.05), bty = "n",
pch = 1, col = 3:1, lty = c(NA, NA, 1),
legend = c(
"Starting parameters",
- "Converged parameters",
+ "Original run",
"Multistart runs"))
}

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