diff options
Diffstat (limited to 'R/parhist.R')
| -rw-r--r-- | R/parhist.R | 42 |
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")) } |