The purpose of this method is to check if a certain algorithm for fitting nonlinear hierarchical models (also known as nonlinear mixed-effects models) will reliably yield results that are sufficiently similar to each other, if started with a certain range of reasonable starting parameters. It is inspired by the article on practical identifiabiliy in the frame of nonlinear mixed-effects models by Duchesne et al (2021).
multistart(object, n = 50, cores = 1, ...)
# S3 method for saem.mmkin
multistart(object, n = 50, cores = 1, ...)
# S3 method for multistart
print(x, ...)
# S3 method for multistart
parms(object, ...)
parhist(object, lpos = "topleft", main = "", ...)
llhist(object, breaks = "Sturges", lpos = "topleft", main = "", ...)The fit object to work with
How many different combinations of starting parameters should be used?
How many fits should be run in parallel?
Passed to the update function, or to the basic plotting function in the case of the graphical functions.
The multistart object to print
Positioning of the legend.
title of the plot
Passed to hist
A list of saem.mmkin objects, with class attributes 'multistart.saem.mmkin' and 'multistart'.
Currently, parallel execution of the fits is only supported using parallel::mclapply, i.e. not available on Windows.
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.