tar_nlmixr_multimodel_parse: Generate nlmixr multimodel target set for all models in one...

In nlmixrdevelopment/nlmixrtargets: Targets for 'nlmixr2' Pipelines

Generate nlmixr multimodel target set for all models in one call to tar_nlmixr_multimodel()

Description

Generate nlmixr multimodel target set for all models in one call to tar_nlmixr_multimodel()

Usage

tar_nlmixr_multimodel_parse(name, data, est, control, table, model_list, env)

Arguments

name	Symbol, name of the target. In tar_target(), name is an unevaluated symbol, e.g. tar_target(name = data). In tar_target_raw(), name is a character string, e.g. tar_target_raw(name = "data"). A target name must be a valid name for a symbol in R, and it must not start with a dot. Subsequent targets can refer to this name symbolically to induce a dependency relationship: e.g. tar_target(downstream_target, f(upstream_target)) is a target named downstream_target which depends on a target upstream_target and a function f(). In addition, a target's name determines its random number generator seed. In this way, each target runs with a reproducible seed so someone else running the same pipeline should get the same results, and no two targets in the same pipeline share the same seed. (Even dynamic branches have different names and thus different seeds.) You can recover the seed of a completed target with tar_meta(your_target, seed) and run tar_seed_set() on the result to locally recreate the target's initial RNG state.
data	nlmixr data
est	estimation method (all methods are shown by 'nlmixr2AllEst()'). Methods can be added for other tools
control	The estimation control object. These are expected to be different for each type of estimation method
table	The output table control object (like 'tableControl()')
model_list	A named list of calls for model targets to be created
env	The environment where the model is setup (not needed for typical use)

nlmixrdevelopment/nlmixrtargets documentation built on Feb. 28, 2025, 5:58 a.m.