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).
parplot(object, ...)
# S3 method for multistart.saem.mmkin
parplot(
object,
llmin = -Inf,
llquant = NA,
scale = c("best", "median"),
lpos = "bottomleft",
main = "",
...
)The multistart object
Passed to boxplot
The minimum likelihood of objects to be shown
Fractional value for selecting only the fits with higher likelihoods. Overrides 'llmin'.
By default, scale parameters using the best available fit. If 'median', parameters are scaled using the median parameters from all fits.
Positioning of the legend.
Title of the plot
Starting values of degradation model parameters and error model parameters are shown as green circles. The results obtained in the original run are shown as red circles.
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.