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 = "",
  ...
)

Arguments

object

The multistart object

...

Passed to boxplot

llmin

The minimum likelihood of objects to be shown

llquant

Fractional value for selecting only the fits with higher likelihoods. Overrides 'llmin'.

scale

By default, scale parameters using the best available fit. If 'median', parameters are scaled using the median parameters from all fits.

lpos

Positioning of the legend.

main

Title of the plot

Details

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.

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.

See also