| pkbuild | R Documentation | 
Fit several structural PK models and select the best one based on a Bayesian Information Criterion. Models to compare can be defined by rate constants and/or clearances and can include or not nonlinear elimination models. See https://monolix.lixoft.com/rsmlx/pkbuild/ for more details.
pkbuild(
  data = NULL,
  project = NULL,
  stat = FALSE,
  param = "clearance",
  new.dir = ".",
  MM = FALSE,
  linearization = F,
  criterion = "BICc",
  level = NULL,
  settings.stat = NULL
)
data | 
 a list with fields 
  | 
project | 
 a Monolix project  | 
stat | 
 (FALSE, TRUE): the statistical model is also built (using buildmlx) (default=FALSE)  | 
param | 
 ("clearance", "rate", "both): parametrization (default="clearance")  | 
new.dir | 
 name of the directory where the created files are stored (default is the current working directory) )  | 
MM | 
 (FALSE, TRUE): tested models include or not Michaelis Menten elimination models (default=FALSE)  | 
linearization | 
 TRUE/FALSE whether the computation of the likelihood is based on a linearization of the model (default=FALSE)  | 
criterion | 
 penalization criterion to optimize c("AIC", "BIC", "BICc", gamma) (default="BICc")  | 
level | 
 an integer between 1 and 9 (used by setSettings)  | 
settings.stat | 
 list of settings used by buildmlx (only if stat=TRUE)  | 
A list of results
## Not run: 
# Build a PK model for the warfarin PK data. 
# By default, only models using clearance (and inter compartmental clearances) are used
warf.pk1 <- pkbuild(data=warfarin)
# Models using elimination and transfer rate constants are used, 
# as well as nonlinear elimination models
warf.pk2 <- pkbuild(data=warfarin,  new.dir="warfarin", param="rate", MM=TRUE)
# Both models using clearances and rates are used. 
# Level is set to 7 in order to get accurate results.
warf.pk3 <- pkbuild(data=warfarin,  new.dir="warfarin", param="both", level=7)
## End(Not run)
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