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).

## Usage

```
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.