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+#' Plot parameter distributions from multistart objects
+#'
+#' Produces a boxplot with all parameters from the multiple runs, scaled using
+#' their medians. If parameter transformations were done by mkin (default in
+#' [saem]), then the parameters found by saem are on the transformed scale, and
+#' scaling is simply done by subtracting the median. If parameter
+#' transformations were done by saemix, scaling is done by dividing by the
+#' median, as in the paper by Duchesne et al. (2021).
+#'
+#' @param object The [multistart] object
+#' @param \dots Passed to [boxplot]
+#' @param main Title of the plot
+#' @param lpos Positioning of the legend.
+#' @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.
+#' doi: 10.1186/s12859-021-04373-4.
+#' @seealso [multistart]
+#' @importFrom stats median
+#' @export
+parhist <- function(object, lpos = "topleft", main = "", ...) {
+  orig <- attr(object, "orig")
+  orig_parms <- parms(orig)
+  start_parms <- orig$mean_dp_start
+  all_parms <- parms(object)
+  median_parms <- apply(all_parms, 2, median)
+  start_scaled_parms <- rep(NA_real_, length(orig_parms))
+  names(start_scaled_parms) <- names(orig_parms)
+
+  if (orig$transformations == "saemix") {
+    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)]
+    boxplot(all_scaled_parms, log = "y", main = main, ...)
+  } else {
+    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)]
+    boxplot(all_scaled_parms, main = main, ...)
+  }
+
+  points(orig_scaled_parms, col = 2, cex = 2)
+  points(start_scaled_parms, col = 3, cex = 3)
+  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",
+      "Multistart runs"))
+}